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Pro Edition FAQ

Qiantong Tech3/10/26About 50 minFAQFAQ

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1. Product Positioning and Business Scenarios

Q: What is qData Data Platform used for?

A: In simple terms, qData is the enterprise "chief data steward".
It brings together data scattered across business systems such as ERP and CRM, cleans it, unifies definitions and classification management, and finally provides high-quality data services to business departments as needed.

It mainly solves three pain points:

  • Breaking data silos: solves mismatched departmental data and conflicting statistical definitions.
  • Improving data quality: eliminates dirty data so data becomes trustworthy and decisions have a solid basis.
  • Reusing data assets: turns accumulated data into assets and avoids repeated work.

💡 Special note:
qData is not only a piece of software, but a complete product system.

  • Core product: the commonly purchased "qData Data Platform Pro Edition" refers to the main platform. It is a complete product that runs independently, with lightweight metadata, master data, and asset management capabilities built in, and it can directly meet most small and medium scenario requirements.
  • Advanced equipment: there are also six independent sub-platforms: Metadata Platform, Tag Platform, Indicator Platform, Master Data Platform, Data Asset Management Platform, and Data Asset Portal Platform. They are the "professional upgrades" of the corresponding modules, designed for more complex and deeper advanced scenarios. You can flexibly combine and purchase them according to actual needs.

Q: What advantages does qData Data Platform have over other data platform products?

A: There are many excellent data platform products on the market, and qData Data Platform learns from and benchmarks against them. Compared with other products, we believe qData Data Platform has the following core characteristics:

  1. 🛡️ Source code delivery, truly independent and controllable
    Source-code licensing turns the data platform from "black-box software" into a technical asset for the enterprise. Source-level delivery plus complete authorization means data infrastructure that truly belongs to the enterprise, enabling independent control and long-term technical accumulation.

  2. 🏗️ Flexible architecture, one-click switching between monolith and microservices
    It uses a monolithic architecture by default for quick startup and verification, while also being tailored for a microservices architecture that can be switched on through simple configuration. It meets agile needs while retaining unlimited scalability, fitting the full journey from small and medium scenarios to enterprise rollout.

  3. 🧩 Complete product system with seven platforms that can be freely combined
    qData is not a single system, but a product system covering the full process of data construction, governance, assetization, and services. It includes seven platforms: Data Platform (main platform), Metadata Platform, Tag Platform, Indicator Platform, Master Data Platform, Data Asset Management Platform, and Data Asset Portal Platform. They can be used independently in lightweight scenarios or flexibly combined; the full suite can better support large and complex projects.

  4. 📚 More than a tool, providing full-lifecycle business support
    It provides not only technical documentation, but also a business support documentation system covering the full process of pre-sales, project initiation, bidding, construction, implementation, reporting, and promotion. This helps customers efficiently complete internal project approval, external bidding, and results reporting, greatly reducing project friction.

  5. 💡 Deep enablement to ensure teams can use it, use it well, and get value
    We do not only sell products; we also provide complete training on basic concepts, system usage, development guidance, and design philosophy. This ensures customer teams can not only deploy the system, but also deeply understand the essence of a data platform and fully realize product value.

  6. 💻 Fully self-developed core, not assembled from open-source pieces
    The core functions are all self-developed, not a simple assembly of third-party open-source projects. Product quality, security, and stability are better protected, while potential risks from open-source components are reduced.

  7. 🚀 Forward-looking technology, refactored and evolved from real practice
    The current Pro Edition was refactored and evolved from an internal 1.0 version accumulated over many years. It adopts a modern, mainstream, and scientific technical architecture, with better scalability and long-term maintenance value.

  8. 🔗 Same AI ecosystem, seamless integration
    qData is a core part of the Qiantong Intelligent Platform Suite and shares the same foundation with qThing, qKnow, qModel, qLabel, qBrain, and other platforms. Used together, they can seamlessly build industry-grade deep AI solutions and reserve ample room for intelligent transformation.

  9. ⚙️ Modular design, lower operations and maintenance costs
    It fully adopts modular design, with internal modules that are highly cohesive and loosely coupled. This greatly reduces the difficulty of later iterative development and system maintenance, making the system lighter and easier to maintain.

  10. 🌐 Mainstream technology stack, high environmental compatibility
    It fully adopts the latest mainstream technology stack, making it more compatible with existing customer and partner environments and reducing integration difficulty and learning costs.

  11. 🔄 Dual-version strategy for diverse needs
    It provides both Open-Source Edition and Pro Edition, meeting the diverse needs of customers with different budgets and stages, so you can flexibly choose the most suitable starting point.

Q: In which industries does qData have real-world implementations?

A: qData is positioned as general-purpose data infrastructure. It is not tightly bound to a specific industry and has strong cross-industry adaptability. Like an enterprise "data operating system", it helps solve common problems such as data silos, inconsistent standards, and difficulty turning data into assets in any industry.

At present, qData has been deeply applied in many key fields, forming mature implementation cases and industry solutions:

  • 🌊 Water conservancy: supports unified watershed data governance and improves decision efficiency for flood control scheduling and water resource management.
  • 🏙️ Smart parks: connects multi-source data such as security, energy consumption, and property management to build a digital twin foundation for parks.
  • 🏭 Intelligent manufacturing: connects ERP, MES, and other systems to make production-process data transparent and enable quality traceability.
  • ⛏️ Coal & ⚡ power: integrates safety production and equipment monitoring data to empower intelligent transformation in the energy industry.
  • 🏥 Healthcare & 🎓 education: breaks down business-system barriers and optimizes full-lifecycle data service experiences for patients and students.
  • 🚦 Transportation and logistics: integrates multimodal transportation data to improve road-network scheduling and logistics collaboration efficiency.

💡 Friendly reminder:
Because business pain points and data scenarios vary greatly across industries, the above are only some typical applications.
If you would like to learn about detailed cases highly matched to your industry (such as concrete construction results or data indicator improvements), or discuss a custom implementation plan, please contact our customer manager directly. We will provide more targeted in-depth communication.

Q: Does qData publish upcoming product plans?

A: qData adheres to the philosophy of long-termism and open co-creation, and regularly publishes product evolution roadmaps covering both the Open-Source Edition and Pro Edition.

  • 🤝 Open co-creation: we sincerely invite industry peers, partners, and customers to participate in discussion and exchange. If you have innovative ideas or specific business requirements, you are welcome to share them with us at any time.
  • 📝 Requirement adoption: our product and R&D team carefully analyzes and evaluates every piece of feedback. Suggestions that fit qData's design philosophy of "general-purpose, efficient, and intelligent" may be included in later version planning, shaping the future of the product together.
  • 🔔 Latest updates: to get the latest product plans, version updates, and event information as soon as possible, follow the Qiantong Tech official WeChat account or join the official product QQ community group.

Q: What is the difference between qData Data Platform Open-Source Edition and Pro Edition? Is upgrading convenient?

A: qData Data Platform provides two forms: Pro Edition and Open-Source Edition, designed to meet the needs of enterprises of different sizes and diverse scenarios. The two editions complement each other and support seamless, smooth upgrades.

🏢 Pro Edition: enterprise-grade all-round expert

  • Positioning: for large-scale, highly complex business scenarios, providing full-link, highly available enterprise-grade solutions.
  • Core Advantages:
    • Complete functionality: covers system management, multi-source heterogeneous data access, advanced modeling, full-link data security, and service governance.
    • Deep enablement: built-in dedicated intelligent capabilities, refined through strict production-environment practice to ensure stable and efficient operation.
    • Premium services: provides vendor-dedicated technical support, customized implementation services, and SLA guarantees.
  • Applicable users: medium and large enterprises, critical business systems, and scenarios with strict requirements for stability and security.

🚀 Open-Source Edition: lightweight introductory mentor

  • Positioning: focuses on core general-purpose functions, emphasizing lightweight use, ease of adoption, and low barriers, helping users quickly get started and practice.
  • Core Advantages:
    • Complete basics: includes basic system management, common data-source access, standard modeling processes, and basic quality checks.
    • Flexible exploration: open and transparent code, suitable for technical verification, learning and research, and fast deployment at small and medium scale.
  • Applicable users: small and medium enterprises, individual developers, university research teams, and startup teams running quick pilots.

🔄 Seamless upgrade: same foundation, smooth evolution

  • Same architecture foundation: Open-Source Edition and Pro Edition are developed based on the same underlying architecture and design philosophy, with consistent core genes and no technology-stack split.
  • Smooth migration: upgrading from Open-Source Edition to Pro Edition can achieve seamless connection. The official team provides dedicated convenient switching and upgrade tools and detailed supporting documentation, helping users complete the transition from "lightweight exploration" to "enterprise-grade application" at low cost and with minimal risk.

💡 Summary

  • Pro Edition is like a senior consultant, providing deep professional capabilities and comprehensive operational assurance.
  • Open-Source Edition is like an introductory teacher, helping you take the first step in data governance at the lowest cost.
  • The upgrade path is a clear expressway, allowing you to easily switch to the more powerful Pro Edition as your business grows.

Whichever edition you choose, qData Data Platform will be a reliable partner that grows with your business and accelerates your digital transformation.

Q: After buying qData Data Platform Pro Edition, why do I still need to buy metadata, master data, and other sub-platforms separately? Aren't these functions built in?

A: This is a very typical and reasonable question. In short: the main platform does indeed "include" these functions, but they are the "standard edition"; the separately purchased sub-platforms are the "professional premium edition".

To help customers spend money where it matters most, we use a "built-in basics + optional advanced capabilities" model:

1. qData Data Platform Pro Edition: practical and cost-effective

  • qData Data Platform Pro Edition (the main platform) is itself an independent and complete product.
  • It has lightweight metadata, master data, asset management, and other core modules built in.
  • Applicable scenarios: for most small and medium enterprises or common scenarios, these built-in functions can fully meet daily data governance and management needs, and you can use them directly without additional payment.

2. Independent sub-platforms (Pro Edition): built for complex scenarios

  • We have upgraded modules such as metadata, tags, indicators, and master data into independent professional sub-platforms.
  • Applicable scenarios: when your enterprise grows, data relationships become extremely complex, or you have deep customization needs in areas such as refined user profiling or full-link lineage analysis, lightweight functions may not be enough. In this case, you can purchase the corresponding "Pro Edition" sub-platforms on demand.

💡 Summary:

We do not force bundled sales because we want to protect customer interests.

  • If you only need to solve basic problems, buying only the main platform is enough, saving money while staying efficient.
  • If you have more advanced needs, you can flexibly combine and purchase the corresponding sub-platforms.

This "choose according to need" approach ensures you only pay for capabilities you truly need.

Q: What products are included in the Qiantong Intelligent Platform Suite? Are they sold externally? Are there open-source plans? How mature are the other platforms besides the data platform?

A: Qiantong Tech is committed to building a full-link intelligent platform system connecting "perception, data, knowledge, and decision-making". The system currently includes six core platforms, with commercialization status, open-source plans, and maturity as follows:

🏢 Qiantong Intelligent Platform Suite overview and commercialization status

Platform nameCore positioningCommercialization statusOpen-source planMaturity assessment
qThing
(IoT Platform)		Foundation for massive device access and perception data collection✅ Commercialized❌ No plan for now⭐⭐⭐⭐⭐
Stable and reliable, supporting large-scale concurrent access
qData
(Data Platform)		Integrated foundation for data governance, modeling, assetization, and services✅ Commercialized
(including Open-Source Edition)		✅ Open-Source Edition available⭐⭐⭐⭐⭐
Highly mature. Includes 7 sub-platforms (main platform + metadata/tags/indicators/master data/assets/portal), all available for flexible purchase
qKnow
(Knowledge Platform)		Knowledge graph + vector database + large model + deep industry applications, building inferable industry knowledge✅ Commercialized
(including Open-Source Edition)		✅ Open-Source Edition available⭐⭐⭐⭐⭐
Highly mature, supporting complex knowledge reasoning and reuse
qModel
(Model Platform)		Full lifecycle management of algorithm models (access/orchestration/deployment/governance)✅ Commercialized
(including Open-Source Edition)		✅ Open-Source Edition available⭐⭐⭐⭐
Feature-complete, supporting multi-model fusion and serviceization
qLabel
(Data Annotation)		High-quality data annotation for algorithm and large-model training🔄 Pre-sale
(large discount available)		📅 Planned⭐⭐⭐
Core functions are ready and commercial adaptation is being optimized
qBrain
(Industry Large Model)		Platform for building and training vertical industry large models🔄 Pre-sale
(large discount available)		📅 Planned⭐⭐⭐
Core training and fine-tuning capabilities are available, and scenario applications are being deepened

💡 Key notes

  • Special note about qData:
    qData is not only an independent product, but also an enterprise-grade data platform product system. Its Pro Edition includes 1 main platform + 6 sub-platforms (metadata, tags, indicators, master data, data assets, and data asset portal). All 7 parts are highly mature and fully commercialized, and customers can purchase them separately or deploy the complete suite as needed.

  • About pre-sale discounts:
    qLabel and qBrain are currently in the final stage of commercialization transformation. The pre-sale channel is now open with significant discounts. Open-source editions are also clearly planned for these two platforms, so please stay tuned.

  • How to get more information:
    If you are interested in details about a specific platform, how to obtain the open-source edition, or the pre-sale discount policy, you are welcome to contact our technical consultants or business managers for in-depth communication.

2. Product Functions and Capabilities

Q: What data source types does qData Data Platform support? If it is not shown on the demo site, does that mean it is unsupported?

A: qData Data Platform Pro Edition is committed to full coverage of mainstream data ecosystems. The demo site only shows some typical examples; data sources not listed there do not mean they are unsupported.

🌟 Core commitments

  • Mainstream full coverage: we already support the vast majority of common data-source types on the market.
  • Free custom support: if a data source required by your business is not listed yet, please purchase with confidence. The official team commits to developing an adapter for you free of charge as soon as possible after contract signing.
    • Time guarantee: the adaptation workload for a single new data source is usually about 5 person-days.
    • Contract backing: the "on-demand custom support" clause can be written directly into the sales contract, protecting your rights in legal form and giving you peace of mind when purchasing.

📊 Typical data sources currently supported include:

  • 🗄️ Relational databases: MySQL, PostgreSQL, Oracle, SQL Server, Dameng (DM8), KingbaseES, DB2, and more;
  • 🚀 Big data engines: Hive, Phoenix (based on HBase), Doris, ClickHouse, and more;
  • 📨 Message queues: Kafka, RabbitMQ, and more;
  • 📁 File storage: FTP, Alibaba Cloud OSS, HDFS, and more;
  • 🛠️ Management tool integration: OSCAR and 15+ mainstream database management tools.

💡 Summary: qData Data Platform has strong extensibility and an agile response mechanism. No matter how complex your current architecture is, we can ensure seamless data access through a "standard support + rapid customization" model.

Q: How do I use qData Data Platform for data integration? What components are available?

A: Data Integration is the core engine of qData Data Platform. It is designed to collect, clean, transform, and output multi-source heterogeneous data. Processed data can be configured as standardized job tasks and, after the review process, accumulated as high-value project assets.

🎨 Zero-code visual operation

  • Drag-and-drop canvas: users do not need to write code. They only drag operators from the component library on the left into the canvas and connect them to build a process.
  • Intelligent execution engine: based on DAG (directed acyclic graph) logic, the system automatically schedules parallel and serial execution between components to ensure efficient and stable processing.

🧩 Massive built-in component library

qData Data Platform includes a very rich set of Data Integration components covering full-link data processing needs:

📥 Input components (all-source access)
Supports access to diverse data sources:

  • Databases: table input component (supporting mainstream databases such as MySQL, Oracle, and PostgreSQL), MongoDB input component, Redis input component.
  • Big data: Hive input component, HDFS input component.
  • Files: Excel file input component, CSV input component.
  • Message queues: Kafka input component, RabbitMQ input component.
  • APIs: API input component.

⚙️ Script and transformation components (deep processing)
Provides powerful data cleaning and logic processing capabilities:

  • Script execution: supports custom logic such as Java script execution.
  • Basic transformations: Join component, sort records, split fields, field derivation, remove duplicate records, row-to-column, column-to-row.
  • Security and generation: field encryption, field decryption, ID generator.
  • Calculation and mapping: calculator, value mapping, add constants, numeric range handling.
  • String processing: string operations, string replacement.
  • Field management: field selection, edit fields, set field values.
  • Intelligent cleaning: built-in templates for 10+ common data cleansing rules.

📤 Output components (multi-end distribution)
Supports flexible writing of processing results to target systems:

  • Databases/storage: table output component, Hive output component, HDFS output component, MongoDB output component, Redis output component.
  • Message queues: RabbitMQ output component.

🤝 Dedicated customization commitment

We commit to continuously supporting all common and mainstream input, output, and transformation components.

  • On-demand extension: if the list above does not cover your specific needs, please contact your customer manager directly.
  • Free development: we will customize and develop the required components for you as soon as possible and will not charge any additional fees, ensuring your business scenario can be implemented smoothly.

Q: What does the "Data Development" function of qData Data Platform mainly do? Which engines does it support?

A: Data Development is one of the core functions of qData Data Platform. It transforms business logic into computing tasks such as SQL and Flink SQL, turning complex data-processing requirements into executable, manageable, and version-controlled code assets.

💻 Web code editor (Web IDE)

Provides a convenient online development environment. Users do not need to install local software, and can complete code writing, debugging, and version management directly in the browser for an efficient Data Development experience.

🚀 Rich execution engine support

Supports mainstream big data computing engines across multiple computing scenarios:

  • Batch processing and offline computing: Spark, Hadoop, Hive
  • Real-time stream computing: Flink, Flink SQL
  • Ad hoc query and analytics: Doris and more

🔗 Deep association and automation

  • Metadata and lineage: automatically parses input and output metadata for tasks, forming clear data lineage relationships.
  • Job Scheduling: after a developed script is published, scheduling nodes can be automatically generated and dependency relationships (DAG) configured, with the scheduling center responsible for timed execution.

🤝 Engine extension commitment

We commit to supporting all common execution engines. If you find that an engine you need is not yet supported, you can contact your customer manager at any time, and we will support and launch it as soon as possible to meet your diverse computing needs.

Q: What is the difference between Data Integration and Data Development?

A: Although they share the same goal (turning raw data into data assets), they differ significantly in processing methods, technical implementation, and applicable scenarios:

  • 🔄 Data Integration (visual ETL)

    • What it does: handles data collection, movement, and basic cleaning, bringing scattered data from business systems into a unified layer, such as the ODS layer.
    • How it works: zero code. Drag input/output components (supporting JDBC, Binlog, API, and more) and configure rules to quickly complete data synchronization.
    • Typical scenarios: synchronizing data from multiple systems to a warehouse, database migration/backup, and source-aligned layer construction.

  • 💻 Data Development (code-based computing)

    • What it does: handles complex business logic computing, processing integrated data into specific business indicators and wide tables.
    • How it works: write code. Deep computation is mainly implemented through SQL (Hive/Spark/Flink), Python, or Shell scripts.
    • Typical scenarios: generating management reports (such as sales statistics and daily active user calculations), complex dictionary mapping, and historical status backtracking and cleaning.

💡 Summary: Data Integration is responsible for "bringing data in and organizing it", solving data silo problems; Data Development is responsible for "calculating data and adding value", solving business insight problems. The two complement each other and jointly build a complete data asset system.

View "Reject the Black Box! Understanding the Difference Between Data Integration and Data Development in One Article"

Q: What does the Data Services function do? What are its core capabilities?

A: Data Services is one of the core functions of qData Data Platform. It converts accumulated data assets into standardized, secure, and controllable APIs for external services. It effectively solves pain points such as data that is "visible but hard to access", repeated API development, and difficult request-log management, significantly improving data reuse, asset value, and reducing R&D costs.

🚀 Core Capabilities

  • 📡 API lifecycle management: supports full-process management from API creation, publishing, and retirement to version control, with rich built-in Data Services categories for easy asset classification and retrieval.
  • 🔒 Secure authentication mechanism: uses the standard OAuth2 protocol for call authentication. The system automatically generates a unique identity (AppKey) and secret (AppSecret) for each application to ensure secure data access.
  • 📊 Operations monitoring and audit: provides detailed Request Logs query functions, monitoring API call volume, response time, and exception status in real time for troubleshooting and usage auditing.
  • 🏢 Application Management: centrally manages caller (application) information and flexibly configures access permissions and quotas for different applications.
  • 📖 Easy integration: automatically generates standardized API integration documentation to help developers quickly complete data-call integration.

With the Data Services module, you can easily publish and manage standardized and efficient data APIs, allowing data assets to truly flow.

Q: Is there a Data Quality module? Does it support quality checks, quality-control rules, and quality reports?

A: Yes. Data Quality is one of the most basic and core functions of qData Data Platform, and we provide full-stack data quality management capabilities.

You can view and use the following core functions in the "Asset Management - Data Quality" module:

  • 🔍 Flexible quality checks: supports scheduled or triggered quality tasks to automatically audit multi-source data.
  • ⚙️ Powerful rule configuration: provides rich built-in rules and supports custom audit rules. You can write scripts such as SQL, Python, and Java to meet quality-control needs in complex business scenarios.
  • 📊 Detailed quality reports: automatically generates multi-dimensional quality reports that clearly show data health, issue distribution, and trend analysis.
  • 🛠️ Closed-loop issue management: provides an issue data visualization dashboard to visually locate abnormal data, and supports marking, alerts, and follow-up handling for issue data, creating a full closed loop from discovery to resolution.

This module can cover most data quality management scenarios and helps you build a trustworthy data asset system.

Q: In Data Quality, problem data can be edited directly in the database. Is this very risky?

A: Yes. Directly editing a production database is a high-risk operation and can easily cause irreversible risks.

  • Damaging data integrity: bypassing the application layer and editing directly may break relationships between tables, such as foreign-key constraints, causing data inconsistency.
  • Causing system failures: incorrect SQL operations, such as accidental deletion or table locking, may directly cause business interruption, application errors, or even permanent data loss.
  • Difficult auditing and rollback: direct edits are often hard to trace, and once an error occurs, it is difficult to roll back through transactions as with application operations, making recovery very costly.

We recommend: to ensure system stability and data security, strictly follow the principle of source governance and correct erroneous data at the source through system-provided functions or standard processes.

Q: What is the Data Assets function?

A: The Data Assets function is a core module of qData Data Platform. It turns scattered, heterogeneous technical data into business assets that are understandable, manageable, and reusable.

🎯 Core value

By unified classification, standardized naming, and complete metadata such as owners and business purposes, it builds an enterprise-grade data asset catalog.

  • Pain-point resolution: solves the problem that business users "cannot find data or understand tables" (for example, locating the exact position of "sales details for the past three years" without repeatedly asking IT).
  • Goal: lowers the threshold for data usage, enabling non-technical users to easily understand and use data, and realizes the transformation from "technical assets" to "business assets".

🛠️ Core functional modules

The main platform includes basic and complete data asset management capabilities, including:

  • 🗺️ Asset Map: globally visualizes data distribution and lineage relationships.
  • 🔍 Data discovery and query: supports keyword search to quickly locate required data tables.
  • ✅ Asset Review: standardizes the data listing process and ensures asset quality.
  • 🛡️ Security and quality: integrates data security grading and quality monitoring capabilities.
  • 🔗 Data Connections: centrally manages multi-source Data Connections information.

💡 Product system description

qData is an enterprise-grade product system covering the full data lifecycle, including: Data Platform (main platform), Metadata Platform, Tag Platform, Indicator Platform, Master Data Platform, Data Asset Management Platform, and Data Asset Portal Platform. The commonly mentioned "qData Data Platform Pro Edition" refers to the main platform (which already includes the basic asset management capabilities above). For more advanced needs, we also provide:

  1. Dedicated Data Asset Management Platform: provides deeper fine-grained management, covering data standards, advanced security policies, and full-link quality governance.
  2. Data Asset Portal Platform: a data asset sharing hall for all staff, providing asset catalog display, resource application, and self-service functions.

You can flexibly choose the built-in functions of the main platform or independent professional platforms according to actual needs.

Q: What does the Data Asset Map do? How is it used?

A: The Data Asset Map is one of the core functions of the data platform. It is designed to centrally register, classify, describe, search, and manage all data assets in an organization. It effectively solves pain points such as scattered data, inconsistent standards, difficult search, and disorderly usage in enterprises.

🚀 Core Capabilities

You can use the following functions in the "Data Assets - Asset Map" module:

  • 🔍 Asset search: quickly locate required data resources.
  • ✏️ Asset maintenance and updates: keep asset information accurate and up to date.
  • 🏷️ Asset tagging: enrich asset dimensions through a tag system for easier classification management.
  • 📢 Asset publishing: officially publish approved assets for all staff to use.
  • 📝 Asset application: supports users initiating data access or usage applications online.

📂 Covered data types

Asset Map fully supports management of three core data types:

  1. Database table data: structured database table information.
  2. External APIs: encapsulated Data Services APIs.
  3. Unstructured data: non-tabular data such as documents, images, and logs.

With Asset Map, you can build a clear enterprise data panorama and make data assets "findable, understandable, and usable".

Q: What does the Job Management function do?

A: Job Management is a core function of the data platform. Its core concept is to orchestrate and combine multiple independent tasks, including Data Integration tasks and Data Development tasks, into one complete "job".

This function is mainly used for centralized orchestration, scheduling, monitoring, and operations of jobs, effectively solving pain points such as scattered tasks, disordered dependencies, repeated development, and difficult maintenance.

🚀 Core value

  • Logical integration: orchestrates scattered tasks into logical business flows, ensuring ordered execution of data links.
  • Efficiency improvement: automates scheduling and collaboration for complex tasks, reducing manual intervention.
  • Reliability enhancement: centrally monitors the full-link status of jobs, quickly locates exceptions, and ensures timely and accurate data output.

🛠️ How to use

You can operate in the "Data Development - Job Management" module. Whether it is simple single-task execution or complex cross-task dependency orchestration, this function can meet management and operations needs in most scenarios.

Q: Does it support collecting API data? Is API-based incremental synchronization available?

A: Yes. qData Data Platform provides complete API data collection capabilities and has a built-in OAuth 2.0 authentication mechanism, allowing secure integration with various open APIs.

📡 Function details

  • API collection: supports configuring complex request parameters and authentication methods to easily obtain external data.
  • Incremental synchronization: supports API-based incremental data synchronization. Note: the prerequisite for incremental synchronization is that the target API itself must provide identifier fields that can be used to recognize incremental data, such as timestamps or auto-increment IDs, so the system can perform breakpoint resume or differential pulling.

🛠️ How to use

In "Data Development - Data Integration Task", select "Add Task" and specify the input source as "API Input". You can then configure and try it in the interface.

Q: Does Data Integration support incremental and full synchronization?

A: Yes. qData Data Platform provides both full synchronization and incremental synchronization, which are the most basic and essential functions in Data Integration.

  • Efficient mechanism: efficient incremental synchronization is implemented based on dynamic cursor technology.
  • Core Advantages:
    • Lower load: significantly reduces pressure on the source database.
    • Improved timeliness: ensures fast data flow and meets real-time requirements.
    • Stable and reliable: natively supports breakpoint resume, effectively reducing the risk of data loss caused by network fluctuations and similar issues.

Q: Does qData Data Platform have BI, Data Visualization, or reporting modules?

A: qData Data Platform has complete BI and Data Visualization capabilities. The corresponding functional module is "Data Visualization".

  • Integration strategy: qData Data Platform does not develop its own visualization engine, but instead chooses to seamlessly integrate with mature mainstream third-party BI products to ensure functional stability, professionalism, and richness.
  • Mainstream support: we plan and support integration with industry mainstream tools including Quick BI, FineReport, and Jimu Report.
  • Flexible adaptation:
    • Current preset: the system currently integrates with Jimu Report (free edition) by default, meeting basic reporting needs.
    • Custom service: if you have a preferred BI tool, whether or not it is on the list, we can provide free adaptation service.
    • Procurement assistance: for scenarios requiring advanced functions or commercial authorization, you can contact the vendor directly or entrust us to assist with procurement and deployment.

Q: Is there a data reporting function? Does it support custom forms?

A: Yes. qData Data Platform provides complete data reporting capabilities, designed specifically to solve data collection problems in business scenarios.

  • Core value: for business staff, it supplements, corrects, and reports structured data manually or semi-automatically. It effectively solves pain points such as data that systems cannot collect automatically, inconsistent data definitions, and data scattered offline in Excel or paper forms, significantly improving data completeness and security while reducing communication and collaboration costs.
  • Main functions:
    • Custom forms: supports flexible configuration of form structures and fields to meet diverse business needs.
    • Task Management: supports publishing collection tasks for efficient data collection and reporting processes.
  • Entry point: you can view and use this function in the system menu "Data Assets > Data Reporting".

Q: What does the Data Standards function do?

A: Yes. Data Standards is one of the most basic and core functions of the data platform.

  • Core role: mainly used to unify enterprise data definitions, structures, and usage rules, focusing on solving problems such as inconsistent indicator definitions, inconsistent field naming, repeated modeling, and difficult data sharing.
  • Business value: by unifying rules and language through this module, ambiguity is eliminated, thereby improving data quality and effectively reducing data maintenance costs.
  • Main functions: covers core capabilities such as standard registration, Logical Model, and Standard Data Element, helping customers manage data standards documents, formulate data standards, and perform data modeling.
  • Usage effect: truly makes data "rule-based", giving users confidence and managers peace of mind.
  • Entry point: you can view detailed functions in the system "Data Standards" module.

Q: What does the Standard Data Element function do? How is it used?

A: Standard Data Element is a core sub-function under the "Data Standards" module (path: Data Standards > Standard Data Element). It is designed to define enterprise data units at the smallest granularity, reusable, and semantically clear level.

In plain terms, Standard Data Elements are the "atomic building blocks" and "common dictionary" of enterprise data, used to uniformly specify what each data field is called, what it looks like, and what it means.

  • Pain points solved: effectively solves problems such as inconsistent naming of the same field across systems, ambiguous meanings, arbitrary basic information configuration, and repeated model construction.
  • Main types:
    • Data element: used for metadata definitions of structured fields, including name, identifier, data type, length, precision, and more, unifying field specifications in physical and logical models.
    • Code table: used for value-domain constraints of enumerated data elements, managing standard code-value mappings in key-value form.
  • Usage method and linkage:
    1. Definition and binding: after completing Standard Data Element definition, fields in the Logical Model can be directly bound to the corresponding Standard Data Element.
    2. Automatic rule inheritance: after a data table is materialized, the system automatically carries related Cleansing Rules and Audit Rules, without repeated configuration:
      • Audit Rules: can be obtained directly in "Data Assets > Data Quality > Data Quality Tasks Add".
      • Cleansing Rules: can be obtained directly in "Data Development > Data Integration Task > Add > Transformation Component".

Through this function, an automated closed loop from standard definition to implementation can be achieved, ensuring consistency of data specifications.

A: Yes. Complete data governance capability is one of the most basic and core functions of qData Data Platform.

The system mainly implements full-process data governance through the following four modules. Among them, Data Integration and Data Development provide powerful visualization and engine support:

  • Data Standards: centrally manages standard documents, Standard Data Elements, and Logical Models to establish data specifications.
  • Data Integration (visual ETL):
    • Operation method: supports visual drag-and-drop orchestration of task processes in the canvas, completing multi-source data access, transformation, cleaning, output, and scheduling.
    • Component capability: the current version supports 4 categories and 41 components, covering full-process configuration:
      • Input components (10 types): support table, Excel/CSV files, Kafka, Hive, HDFS, API, MongoDB, Redis, RabbitMQ, and other multi-source access.
      • Transformation components (24 types): cover field derivation, encryption/decryption, row-to-column, deduplication, Join, string processing, and other rich processing capabilities.
      • Script component (1 type): supports executing Java scripts.
      • Output components (6 types): support writing to tables, Hive, HDFS, MongoDB, Redis, RabbitMQ, and other targets.
    • Runtime configuration: supports selecting execution engines such as Spark and Flink, and finely configuring Driver/Executor resources, Yarn queues, retry policies, and schedule cycles.
  • Data Development (WebIDE):
    • Operation method: provides an online WebIDE for data-processing scenarios, supporting code writing through SQL or scripts, with code editing, template reference, debugging, and publishing integrated.
    • Engine support: supports multiple computing engines such as DM8, Oracle, MySQL, Hive, SparkSql, and Flink, applicable to batch processing, stream processing, and reporting scenarios.
    • Functional features: supports quick initialization from task templates, multi-condition task filtering, fine-grained resource parameter configuration such as cores, memory, and queues, and complete scheduling lifecycle management.
  • Data Quality: automatically detects and monitors data assets based on preset Audit Rules to ensure continuous high quality.

Through close linkage of the above steps, qData Data Platform helps enterprises build a complete governance system from "standard definition" to "efficient development" and then to "quality closed loop".

Q: Is there a metadata management function?

A: Yes. qData Data Platform provides multi-level metadata management capabilities from "built-in lightweight management" to an "independent professional platform".

  • Built-in lightweight capability (main data platform):
    qData Data Platform Pro Edition (the main platform) includes basic metadata management functions, which can automatically organize data tables, fields, business definitions, and lineage relationships. This helps users quickly understand and confidently use data, and lays a foundation for later governance.

  • Professional advanced capability (Metadata Platform):
    The qData product system includes an independent Metadata Platform, designed for scenarios requiring fine-grained management. Used together with the main platform, it can significantly deepen governance, for example:

    • raises data lineage granularity from the database/table level to the field level.
    • supports metadata management for unstructured data.
    • provides more comprehensive metadata collection, analysis, and governance capabilities.

Note: qData is an enterprise-grade data platform product system covering the full process of data construction, governance, assetization, and services. It includes seven platforms: Data Platform, Metadata, Tags, Indicators, Master Data, Data Assets, and Data Asset Portal. If you have advanced needs such as field-level lineage or unstructured data management, we recommend purchasing the Metadata Platform together with the main platform. Please contact your customer manager for specific requirements.

Q: Is there a data lineage function? How detailed can it be?

A: Yes. Data lineage is one of the core functions of qData Data Platform. It is mainly used for data tracing and impact analysis, and is divided into two levels by precision: table-level and field-level:

  • Table-level lineage (built into the main platform):
    qData Data Platform Pro Edition (the main platform) supports table-level lineage by default. You can directly view and analyze flow relationships between tables in "Asset Map → Asset Details → Data Lineage", meeting most daily traceability needs.

  • Field-level lineage (requires the Metadata Platform):
    If you need more refined field-level lineage that precisely tracks the source and destination of specific fields, you need to additionally purchase the Metadata Platform in the product system. Used together with the main platform, it can raise lineage analysis granularity from "tables" to "fields", enabling deeper fine-grained governance.

Note: qData is an enterprise-grade product system covering the full data lifecycle, including seven platforms: Data Platform (main platform), Metadata, Tags, Indicators, Master Data, Data Assets, and Data Asset Portal. The main platform provides basic general governance capabilities, while the Metadata Platform and other sub-platforms provide advanced professional capabilities. If you have advanced needs such as field-level lineage, we recommend combined purchase. Please contact your customer manager for specific requirements.

Q: Is there an impact analysis function?

A: Yes (requires the Metadata Platform). Impact analysis is an advanced governance capability. It is mainly used to accurately evaluate the potential impact of data changes on downstream systems, reports, models, or business processes before changes are made.

  • Capability description:
    Complete impact analysis depends on fine-grained field-level metadata relationships. Because the qData Data Platform main platform (Pro Edition) focuses on basic general metadata management with relatively coarse granularity, it does not directly include complete impact analysis functions.

  • How to obtain it:
    To use this function, we recommend purchasing the Metadata Platform in the product system. Through deep fine-grained metadata governance, such as building field-level lineage, this platform can seamlessly collaborate with the main platform and provide strong impact analysis capabilities, helping you reduce change risk.

Note: qData is an enterprise-grade product system covering the full data lifecycle, including Data Platform, Metadata, Tags, Indicators, Master Data, Data Assets, and Data Asset Portal. The main platform provides basic capabilities, while the Metadata Platform and other sub-platforms provide advanced professional capabilities. If you have advanced needs such as impact analysis, we recommend combined purchase. Please contact your customer manager for specific requirements.

Q: Is there a tag management function?

A: Yes (requires the Tag Platform).

  • Function description:
    The qData Data Platform main platform (Pro Edition) does not include tag management. Complete tag management capabilities are provided by the independent Tag Platform.

  • How to obtain it:
    To centrally tag data, indicators, and business objects and build an enterprise-grade tag system, you need to purchase the Tag Platform. This platform is an advanced application designed for fine-grained tag governance. Used together with the main platform, it helps you quickly search, classify, understand, and reuse data assets, upgrading tag management from "none" to "professional".

    • Linkage value: the Tag Platform can also deeply integrate with the Indicator Platform, forming a complete closed loop of "indicator definition → tag production → business application", significantly improving the business conversion value of data assets.

Note: qData is an enterprise-grade product system covering the full data lifecycle, including Data Platform (main platform), Metadata, Tags, Indicators, Master Data, Data Assets, and Data Asset Portal. The main platform focuses on Data Development and basic governance, while the Tag Platform and other sub-platforms provide professional advanced capabilities in vertical fields. If you have advanced needs such as building complex user profiles or refined operations, we recommend combined purchase. Please contact your customer manager for specific requirements.

Q: Where are data tags and data feature construction included?

A: Supported through the independent Tag Platform.

  • Function description:
    The qData Data Platform main platform (Pro Edition) focuses on Data Development and basic governance, and does not include tag management. Complete tag and feature construction capabilities are provided by the independent Tag Platform.

  • How to obtain it:
    To centrally tag data, indicators, and business objects and build an enterprise-grade tag system, you need to purchase the Tag Platform. This platform is an advanced application for fine-grained tag governance. Used together with the main platform, it helps you quickly search, classify, understand, and reuse data assets, upgrading tag management from "none" to "professional".

    • Linkage value: the Tag Platform can also deeply integrate with the Indicator Platform, forming a complete closed loop of "indicator definition → tag production → business application", significantly improving the business conversion value of data assets.

Note: qData is an enterprise-grade product system covering the full data lifecycle, including Data Platform (main platform), Metadata, Tags, Indicators, Master Data, Data Assets, and Data Asset Portal. The main platform focuses on Data Development and basic governance, while the Tag Platform and other sub-platforms provide professional advanced capabilities in vertical fields. If you have advanced needs such as building complex user profiles or refined operations, we recommend combined purchase. Please contact your customer manager for specific requirements.

Q: Is there an indicator management function?

A: Yes (requires the Indicator Platform).

  • Function description:
    The qData Data Platform main platform (Pro Edition) does not include indicator management. Complete indicator management capabilities are provided by the independent Indicator Platform.

  • How to obtain it:
    To centrally manage indicator definitions, calculation logic, and lifecycle and build an enterprise-grade indicator system, you need to purchase the Indicator Platform. As an advanced application designed for fine-grained indicator governance, it can seamlessly collaborate with the main data platform and upgrade indicator management from "none" to enterprise-grade standards.

    • Linkage value: the Indicator Platform can also deeply integrate with the Tag Platform, forming a complete closed loop of "indicator definition → tag production → business application", significantly enhancing direct business support from data.

Note: qData is an enterprise-grade product system covering the full data lifecycle, including Data Platform (main platform), Metadata, Tags, Indicators, Master Data, Data Assets, and Data Asset Portal. The main platform focuses on Data Development and basic governance, while the Indicator Platform and other sub-platforms provide professional advanced capabilities in vertical fields. If you need unified indicator definitions or an indicator system, we recommend combined purchase. Please contact your customer manager for specific requirements.

Q: Is there a Master Data Platform?

A: Yes. qData Data Platform provides multi-level master data management capabilities from "built-in basic management" to an "independent professional platform":

  • Built-in basic capability (included in Pro Edition):
    qData Data Platform Pro Edition (the main platform) includes basic master data management functions, meeting daily core entity data maintenance and simple governance needs.

  • Professional advanced capability (independent Master Data Platform):
    If you need to solve complex problems such as inconsistency, duplication, and fragmentation of core business entity data and build an enterprise-grade master data system, you can additionally purchase the independent Master Data Platform. As an advanced application for fine-grained master data governance, it can work with Pro Edition to upgrade management capability from "usable" to enterprise-grade standards.

Note: qData is an enterprise-grade product system covering the full data lifecycle, including Data Platform (Pro Edition), Metadata, Tags, Indicators, Master Data, Data Assets, and Data Asset Portal. Pro Edition provides basic general capabilities, while the Master Data Platform and other sub-platforms provide professional advanced capabilities in vertical fields. If you have advanced needs such as unified core data definitions or building golden records, we recommend combined purchase. Please contact your customer manager for specific requirements.

Q: Is there a resource portal platform?

A: Yes, but it requires the Data Asset Portal Platform.

  • Function description:
    qData Data Platform Pro Edition does not include an independent resource portal or asset portal view. Complete asset portal service capabilities are provided by the independent Data Asset Portal Platform.

  • How to obtain it:
    To solve problems such as scattered digital assets, unsynchronized information, and low access efficiency, and to build a unified enterprise-grade Data Services window, you need to purchase the Data Asset Portal Platform. This platform is an advanced application for asset operations and services. Used together with Pro Edition, it can significantly improve the visibility, usability, and business conversion value of data assets.

Note: qData is an enterprise-grade product system covering the full data lifecycle, including Data Platform (Pro Edition), Metadata, Tags, Indicators, Master Data, Data Asset Management, and Data Asset Portal. Pro Edition focuses on Data Development and basic governance, while the Data Asset Portal Platform and other sub-platforms provide professional advanced capabilities in vertical fields. If you have advanced needs such as building a unified data marketplace or improving asset operations efficiency, we recommend combined purchase. Please contact your customer manager for specific requirements.

Q: Does qData Data Platform have an AI module?

A: Yes, and it is a strategic core direction.

  • Strategic planning:
    AI-driven capabilities and AI-oriented data governance are major strategic directions of qData Data Platform. In product planning, AI capabilities are being deeply integrated into every part of the data platform to comprehensively promote intelligent innovation.

  • Requirement response mechanism:
    If you have specific AI function needs that are not yet reflected in the current version, you are welcome to discuss them with us.

    • Free iteration: for common needs that are consistent with the qData product system planning direction, we will include them in the priority iteration plan, provide support as soon as possible, and charge no additional fees.
    • Co-creation promotion: we sincerely invite users to participate and jointly promote AI transformation and innovation implementation for the data platform.

Q: Does qData Data Platform support governance of unstructured data?

A: Fully supported.

  • Support scope:
    The system supports integration with multiple file systems such as object storage, HDFS, and FTP, and performs unified governance on unstructured data in them.

  • Core Capabilities:
    Mainly covers standardization of catalog levels and file names, as well as key governance scenarios such as batch/incremental synchronization, deduplication, and filtering of files.

  • Operating mechanism:
    Uses a "configuration scheduling + engine execution" model. Specific governance computing is completed by Spark or Flink batch engines. qData is responsible for task configuration and scheduling and does not participate in specific file storage.

Q: Does qData Data Platform support collecting data directly from devices?

A: Direct collection is not supported.

  • Function positioning:
    qData Data Platform focuses on the core capabilities of a data platform and does not include collection functions that directly connect to IoT devices through protocols such as MQTT or Modbus. This type of device access usually belongs to an IoT platform such as Qiantong qThing.

  • Recommended architecture:
    We recommend a layered architecture of "IoT Platform + Data Platform":

    1. Device access layer: first complete device connection and protocol parsing through a professional IoT platform such as qThing.
    2. Data transmission layer: push parsed data to message queues such as Kafka.
    3. Data platform layer: qData directly accesses data from the message queue for subsequent cleaning, development, and governance.

Q: How are Audit Rules and Cleansing Rules applied in Data Development? Can rules be added?

**A: **

  • Audit Rules(Data Quality)

    • Purpose: used for quality detection and validation of data assets. If data does not meet preset standards, the system automatically marks it as "exception" or "warning".
    • Application path: Data Assets > Data Quality > Data Quality Rules > Add.

  • Cleansing Rules(Data Integration)

    • Purpose: applied in Data Integration tasks to automatically or semi-automatically correct, standardize, complete, or delete collected data.
    • Application path: Data Development > Task Management > Data Integration Task > Add (called in task configuration).

  • About adding rules

    • Pure configuration-based adding is not supported: because each rule depends on independent business logic, the system does not currently support creating entirely new rule types only through interface configuration.
    • Secondary development extension: to add custom rule types, follow the official development specifications and extend and register them through code-based secondary development.

Q: Does qData Data Platform have a data comparison function?

A: Native comparison functionality is planned. For now, we recommend automated monitoring through "quality consistency checks".

  • Current status and plan:
    For traditional row-by-row difference comparison between tables or within a table, the system does not directly support it yet. This function has been included in the product plan and is expected to launch soon, around 10 business days.

  • Best-practice recommendation:
    Considering that traditional full data comparison is inefficient and difficult to run continuously over the long term, we recommend a more efficient and sustainable data quality management solution:

    • Configure consistency rules: use the Data Asset Management > Data Quality module to configure consistency check rules, such as comparing source and target row counts or aggregated values of key fields.
    • Automated monitoring and alerts: the system regularly executes validation tasks automatically. Once data inconsistency is found, it immediately triggers an alert notification, without manual judgment of comparison results, enabling long-term monitoring of data consistency.

Q: Does qData Data Platform have data mining or machine learning modules?

A: Not built in for now. It focuses on data governance and high-quality data supply.

  • Product positioning:
    qData is positioned as an enterprise-grade data platform, mainly focusing on full-domain data governance capabilities such as integration, standards, quality, and security, rather than directly providing data mining or machine learning algorithm engines.

  • Ecosystem collaboration solution:
    Although qData does not include algorithm models, it has strong Data Services capabilities:

    • Standardized API output: provides standardized Data Services APIs.
    • Empowering AI platforms: can seamlessly deliver deeply governed high-quality data to mainstream professional AI training platforms or data mining tools, helping upper-layer intelligent applications be built efficiently.

3. Technical Architecture and Integration Capabilities

Q: How is the performance of qData Data Platform? Can it meet large data volume or high timeliness requirements?

A: The architecture is stable. Performance depends on underlying resources and architecture design, and professional optimization services are supported.

  • Performance positioning:
    As the management layer of the data platform, qData does not directly execute massive big data computing itself, and its system architecture is stable. Overall performance mainly depends on resource configuration of the underlying big data platform, data structure design, and calling methods.

  • Built-in optimization capabilities:
    The platform provides rich performance tuning parameters and supports flexible user configuration:

    • Task resource isolation: fine-grained allocation of computing resources.
    • API caching strategy: improves response speed for high-frequency queries.
    • Microservice deployment: supports elastic scaling for high-concurrency scenarios.

  • Implementation recommendations and services:

    • Early planning: we recommend that the implementation team centrally plan the underlying data architecture at the beginning of the project and formulate a controllable overall performance plan based on platform capabilities.
    • Professional services: for large data volume or high timeliness needs in complex scenarios such as water conservancy, manufacturing, and government affairs, we can provide paid performance optimization technical support and consulting services, helping identify system bottlenecks and provide professional recommendations to ensure stable business operation.

View"qData Performance Bottleneck Analysis and Tuning"

Q: Which execution engines does qData Data Platform support?

A: It is compatible with mainstream ecosystems (Flink/Spark/Hive), enabling unified batch-stream development and elastic scheduling.

  • Engine compatibility:
    qData fully supports mainstream big data computing engines such as Flink, Spark, and Hive, flexibly covering the two major business scenarios of offline batch processing and real-time stream processing.

  • Unified management and control capability:

    • Offline computing: mainly relies on Spark and Hive engines to process massive historical data.
    • Real-time computing: mainly relies on the Flink engine to process low-latency streaming data.
    • Integrated scheduling: the platform provides a unified development interface and scheduling center, allowing users to implement "batch-stream integrated" task development and operations management without switching tools.

  • Deployment flexibility:
    Uses an on-demand deployment strategy. Customers can choose specific engine components according to actual business load. The system does not force binding to all engines, effectively saving resource costs.

  • Extension support:
    If your business scenario involves special execution engines outside the list above, please contact your customer manager for customized evaluation and adaptation support.

Q: Are all tasks in Data Integration, Data Development, and Data Quality distributed computing tasks?

A: Yes. Full-link tasks are based on a distributed architecture and have elastic scalability.

  • Distributed execution mechanism:
    All tasks in the Data Integration, Data Development, and Data Quality modules are dispatched through the unified scheduling system to the underlying distributed computing engines for execution.

    • Core engines: include Spark (batch processing), Flink (stream/batch processing), Hive, Hadoop MapReduce, and more.
    • Database adaptation: for read/write operations on specific database engines, it also supports efficient transmission using their own parallel processing capabilities or distributed gateways.

  • Performance and scalability guarantee:
    Because the underlying execution engines naturally have distributed characteristics, tasks automatically use multi-node cluster resources for parallel processing during execution.

    • High performance: can easily handle massive data-processing needs.
    • Elastic scaling: supports horizontal scaling (scale-out) at any time according to business load. Adding cluster nodes can linearly improve computing capacity, so performance bottlenecks are not a concern.

Q: Which databases are supported for the system runtime environment?

A: MySQL and Dameng (DM8) are supported. Dameng is recommended by default for Xinchuang scenarios.

  • Support list and versions:

    • Dameng database: supports DM8 (the system default configuration).
    • MySQL database: supports versions 5.7 and 8.0.

  • Selection recommendations:

    • Xinchuang and production scenarios: prefer Dameng. As a domestic database, it fully meets Xinchuang compliance requirements and better fits the stability and security needs of mainstream domestic government and state-owned enterprise application scenarios.
    • Validation and development scenarios: MySQL can be selected. Because it is widely used, open source, and free, it is convenient for customers to quickly build an environment for function validation, testing, or learning.

  • Extension support:
    If your project has special database adaptation needs, such as other domestic databases or specific versions, we can provide customized services to help evaluate and extend support for new runtime databases.

Q: Which big data components does the full functionality of Data Platform Pro Edition depend on? What are the corresponding versions?

A: The core dependencies are DolphinScheduler and Spark, while other components are optional as needed.

  • Required components (minimal deployment):

    • Task scheduling: DolphinScheduler (secondary development based on version 3.2.2). It is responsible for full-link task orchestration, scheduling, and monitoring, and does not directly process data.
    • Data computing: Spark. It is responsible for core offline data computing and processing tasks.
    • Note: deploying only the two components above can meet basic Data Development and scheduling needs.

  • Optional components (extended on demand):

    • Real-time computing: Flink. If the business involves real-time stream processing, the Flink engine must be deployed additionally.
    • Other ecosystems: Hive, Hadoop, and others can be flexibly selected according to specific data sources and processing scenarios, and are not mandatory dependencies.

  • Deployment strategy:
    qData uses a modular architecture and supports flexible combinations of underlying components according to business scenarios (offline/real-time). The specific dependency list and version requirements will be based on the final approved "deployment implementation plan".

Q: Does the system mandatorily depend on certain basic components?

A: Yes. System operation strongly depends on a database, Redis, RabbitMQ, and a scheduler. Computing engines can be selected as needed.

  • Core required components:
    The following components are necessary prerequisites for stable system operation. If missing, core functions will be unavailable:

    • Database: stores metadata and configuration information (supports MySQL/Dameng).
    • Redis: provides high-speed caching services to ensure system response performance.
    • RabbitMQ: handles message queue transmission. If not deployed, task status updates will fail directly and logs cannot be synchronized.
    • DolphinScheduler: acts as the core scheduling engine. If missing, all data tasks cannot be scheduled or executed.

  • Optional components selected on demand:

    • Spark: as an offline computing engine, it is not mandatory. Users can choose whether to deploy it according to actual business scenarios, such as only needing real-time computing or only doing Data Integration.

  • Summary:
    The infrastructure layer (storage, cache, messaging, scheduling) must be fully deployed to ensure platform availability, while the computing engine layer, such as Spark and Flink, supports flexible trimming according to business load.

Q: Does qData Data Platform support managing data warehouses?

A: Yes. qData Data Platform is positioned as a "data warehouse manager". It can centrally manage mainstream data warehouses rather than replacing storage and computing facilities.

  • Core positioning: separation of management and execution

    • qData (management layer): as enterprise-grade data platform software, it is responsible for sending scheduling instructions, metadata collection, and task orchestration, and does not directly undertake underlying storage and computing for massive data.
    • Data warehouse (execution layer): as infrastructure, it receives qData instructions and passively executes specific data storage and computing tasks.
    • Relationship summary: qData is the "commander" and the data warehouse is the "executor". The two work together, and qData is designed to manage rather than replace the data warehouse.

  • Core value: unified metadata view

    • Multi-source integration: automatically connects to and integrates metadata from mainstream data warehouses through metadata collection technology.
    • One-stop management: users do not need to log in to multiple independent database systems separately. They can globally view, search, and manage structures and assets of all data warehouses in the qData unified interface, greatly improving management efficiency.

Q: Why does qData Data Platform choose DolphinScheduler as the scheduling engine? How was the scheduling selection considered?

A: After comprehensive comparison with mainstream solutions such as Airflow and Oozie, qData Data Platform finally selected DolphinScheduler mainly because of its excellent ecosystem compatibility, stable dependency control, and large-scale scheduling capability.

  • Broad component compatibility
    DolphinScheduler provides native and deep support for various big data components such as Spark, Flink, Hive, and Hadoop. It can seamlessly adapt to qData's complex heterogeneous computing scenarios and reduce integration costs.

  • Complete dependency control and high stability
    Its visual workflow design provides a more intuitive and rigorous task dependency control mechanism. Compared with other engines, it performs stricter logic validation when handling complex links, delivers higher system stability, and effectively reduces task error rates.

  • Capable of complex scenarios and large-scale scheduling
    For the high-concurrency requirements of enterprise-grade data platforms, DolphinScheduler shows strong horizontal scalability. It can stably support complex task orchestration and large-scale concurrent scheduling of massive tasks in qData Data Platform, ensuring efficient production operation.

Q: How do I operate multiple data source table inputs?

A: The platform natively supports parallel input from multiple data sources, which can be quickly configured through visual drag-and-drop.

  • Operation path:
    Open Data Development > Task Management > Data Integration Task, then click Add to open the task editing page.

  • Configuration steps:

    1. In the component bar on the left side of the canvas, find Input Component.
    2. Drag the component into the canvas multiple times; each dragged component represents an independent data source table.
    3. Click each input component separately and configure the corresponding data source connection and target table information.
    4. Connect the output lines of multiple input components to downstream processing or output components to complete unified access to multi-table data.

Q: Does qData Data Platform have big data management functions?

A: qData focuses on "logical management and scheduling" of data assets, and is not responsible for "physical deployment and operations" of the underlying big data platform.

  • Product positioning: integration rather than replacement

    • Databases, data warehouses, and big data computing platforms such as Hadoop/Spark clusters are underlying infrastructure, usually planned and deployed centrally by the customer.
    • qData Data Platform connects and integrates with these infrastructure components through standard APIs. It is responsible for upper-layer task scheduling, metadata management, and Data Development, and does not directly take over installation, configuration, or hardware operations of the underlying platform.

  • Service boundary description

    • Standard product scope: does not include implementation work such as building the big data base environment, capacity expansion, or underlying troubleshooting.
    • Value-added service support: if you need overall planning, deployment implementation, or managed maintenance services for a big data platform, our team has the corresponding professional capabilities and can provide them separately as independent paid service projects.

4. Security, Compliance, and Stability

Q: Does qData Data Platform have Data Security functions? What are they used for?

A: Yes. qData Data Platform includes a complete data security management system, covering core functions such as data classification, grading, intelligent recognition rules, and desensitization strategies.

  • Function entry and closed-loop process

    • Operation path: open the Data Assets > Data Security module.
    • Automated closed loop: the system uses the full-process automation mechanism of "full data scan → feature matching and recognition → automatic category hit → intelligent grading and tagging" to precisely control sensitive data.

  • Core value: reduce costs, improve efficiency, and avoid risk

    • Pain points solved: when facing massive and structurally complex database assets, traditional manual field-by-field sensitivity identification is inefficient, costly, and error-prone.
    • Main benefits:
      1. Efficiency improvement: automated recognition greatly reduces manual sorting and operations workload.
      2. Security assurance: accurate automatic grading and desensitization effectively build a data protection barrier, significantly reducing data leakage risk and ensuring compliant use.

Q: Has the product passed classified protection certification?

A: The underlying architecture and security functions of qData Data Platform fully meet classified protection compliance requirements, and we have mature experience assisting with certification.

  • Ready capabilities and successful cases
    The product has built-in security mechanisms that meet classified protection standards. At present, multiple customers have successfully passed classified protection certification with our assistance, validating the product's compliance implementation capability.

  • Full-process cooperation and support
    Classified protection certification must be led by the customer and entrusted to a third-party organization. If your company has certification needs, we will fully cooperate by providing required technical documents, assisting with security hardening, responding to rectification requirements from the evaluation organization, and helping you obtain the certificate smoothly.

  • Mainstream certification planning
    For mainstream classified protection levels commonly used in the industry, we are also planning independent certification initiated by the vendor side to further reduce customers' compliance costs.

Q: The Pro Edition demo system is unstable and has errors. Is it incomplete development or a bug?

A: qData Data Platform Pro Edition is highly mature and can fully meet the needs of various commercial scenarios. The demo system stays synchronized with the latest official version and is not an unfinished product.

  • Reasons for fluctuations
    The demo environment is a multi-user shared resource. Occasional instability or errors usually come from instant high concurrency, network fluctuations, resource contention, or dirty data interference generated by other trial users, rather than functional defects in the product itself.

  • Feedback and handling
    If you encounter such problems, please contact us promptly through the QQ Community Group or Enterprise WeChat. The technical team will investigate immediately, clean up interfering data, or optimize resource configuration to ensure a smooth experience.

  • Premium testing plan
    If you need an absolutely stable, isolated, and exclusive system environment for in-depth testing or function validation, please ask about our short-term private deployment service. We will build a dedicated test environment for you.

Q: Can qData Data Platform Open-Source Edition be used commercially?

A: qData Data Platform Open-Source Edition is free and allowed for commercial use, but unauthorized editing of the Logo and copyright information is strictly prohibited.

  • Commercial use and brand boundaries
    We follow the philosophy of "lightweight, truly open source, and commercially usable", opening core code for free use. But open source does not mean giving up attribution. Removing or replacing brand identifiers such as Logo and copyright information without official authorization constitutes infringement. If brand customization is required, such as removing or replacing branding, please purchase a Brand Customization License from the official team.

  • Common industry practice
    "Opening code capabilities while retaining brand ownership" is a common practice among mature open-source projects such as Elasticsearch, GitLab, MongoDB, and Redis. This protects the free flow of technology while maintaining the legitimate rights of the original creators.

  • Summary
    You have the right to use the technology, and we retain the right of brand attribution. Please use it commercially with confidence while following brand rules. For customization needs, contact the official team to obtain proper authorization.

Q: Does the system support multi-tenancy?

A: qData currently has no plan for a multi-tenancy architecture. Instead, it uses a "project space" isolation mechanism to meet collaboration needs.

  • Product positioning and strategy
    qData Pro Edition focuses on ToB private deployment scenarios. In this mode, we do not recommend or need a traditional multi-tenant architecture. Instead, we provide independent deployment instances for each customer or large organization to ensure the highest level of data sovereignty and security.

  • Alternative: project space isolation
    For collaboration needs among different teams or business lines within the same deployment instance, we use the "project space" function to implement logical isolation.

    • Resource isolation: data, tasks, and permissions in different project spaces are independent and invisible to each other.
    • Efficient collaboration: this protects data security boundaries for each business group while sharing underlying computing and storage resources, fitting parallel use cases across multiple departments inside an enterprise.

A: The original code and core intellectual property of qData Data Platform belong to us, so customers cannot apply for software copyright for them; however, independently developed innovative modules based on it can be applied for separately.

  • Ownership definition
    qData Data Platform is our self-developed product and has obtained national software copyright registration (registration number: Software Copyright Registration No. 16069171). Purchase authorization only grants you the right to deploy, run, maintain, and conduct secondary development. The intellectual property of the original code and its derivative edited versions still fully belongs to us and cannot be used as your own achievement to apply for software copyright.

  • Eligible declaration scope
    If you independently develop new standalone functional modules based on qData Data Platform, and they do not edit or include original core code, the added parts can be separately applied for as your independent software copyright achievements.

  • Usage restrictions
    Any secondary development results based on qData Data Platform are limited to internal business use. External sales, source-code transfer, or use in commercial scenarios that directly compete with us is strictly prohibited and will be deemed a breach of contract.

5. Delivery, Operations, and Business Services

Q: How much does Pro Edition cost?

A: Specific Pro Edition quotes must be obtained from a customer manager. We provide two flexible authorization models:

  • How to obtain it
    The product information package, including the "quotation sheet" and "sales contract template", is not publicly downloadable. Please click the link below to add Enterprise WeChat, and a dedicated customer manager will send you the complete materials.
    Click here to add Enterprise WeChat and get materials

  • Authorization models

    • Enterprise source code authorization: delivers complete source code and supports deep customization and secondary development.
    • Enterprise installation package authorization: delivers compiled standard installers, ready to use with convenient operations.
    • Note: the two models use different pricing strategies. Specific prices are subject to the latest quotation provided by the customer manager.

  • Consultation support
    After adding the contact, you can communicate with the customer manager at any time about selection recommendations, business terms, and customization needs.

Q: Can the qData product price be discounted?

A: qData uses unified pricing across all channels and does not currently provide price discounts or special promotions, ensuring consistent service standards for all customers.

  • Pricing principle
    Our pricing system is based on "long-term service" and "sustainable delivery". Unified pricing is intended to ensure every customer receives the same product capabilities, delivery resources, and technical support standards, avoiding uneven service quality or project investment caused by price differences.

  • Value proposition
    For us, price is not the focus of negotiation. We are more committed to providing sound business value through stable product capabilities and long-term service assurance.

Q: What is the qData authorization mechanism? Can you explain it in detail?

A: qData provides two flexible authorization models. You can learn the details in the following ways:

  • Brief description
    Please directly refer to the second page of the "quotation sheet" in the product information package, where the core summary of the authorization mechanism is included. The price sheet distinguishes the following two authorization methods, with different pricing:

    • Enterprise source code authorization: delivers complete source code and supports deep customization and secondary development.
    • Enterprise installation package authorization: delivers compiled standard installers, ready to use with convenient operations.

  • Get detailed explanation
    To understand the complete authorization terms, details, and applicable scenarios, please contact your customer manager to obtain the complete product information package. The package includes dedicated "authorization explanation documents" for in-depth review.

Q: Does Pro Edition provide source code?

A: Yes. Pro Edition supports a source code authorization model.

  • Delivery content
    After completing the source code authorization purchase for Pro Edition, we will deliver the complete source code to you.

  • Development benefits
    You can conduct in-depth secondary development and customization based on the source code, with no functional restrictions, fully meeting your personalized business needs.

Q: Does the authorization include third-party components such as Dameng?

A: No.

  • Product positioning difference
    qData is positioned as a data platform product, with its core focus on data governance capabilities. Databases such as Dameng and big data components belong to underlying storage or computing engines (infrastructure).

  • Authorization scope
    Therefore, qData product authorization only covers the platform software itself and does not include authorization for third-party infrastructure components such as Dameng. Such components must be purchased separately by users or deployed based on the existing environment.

  • Detailed basis
    Specific component dependencies and responsibility boundaries are subject to the relevant terms in the final signed contract.

Q: Does Pro Edition authorization include a Brand Customization License?

A: Yes. All Pro Edition authorization models include a Brand Customization License.

  • Customization benefits
    After obtaining Pro Edition authorization, you can freely edit the Logo and copyright information in the system to match your enterprise image, without paying additional fees.

  • Intellectual property statement
    Please note that brand customization only involves adjustments at the interface display level, and the core intellectual property of the product still belongs to us. Therefore, the specific usage scope, customization depth, and compliance requirements must strictly follow the relevant terms in the sales contract.

Q: Does the system support one-time buyout?

A: No.

The system currently only provides two models: source code authorization and installation package authorization. Intellectual property always belongs to Qiantong Tech (specific ownership is detailed in the sales contract), so a "buyout" service cannot be provided.

  • Service model
    The above authorizations all include one year of free update service. After expiration, if you need to continue receiving new versions, functional upgrades, and security patches, you need to purchase an annual subscription service.

  • Brief explanation
    Software products require continuous iterative R&D and technical investment. The "authorization + subscription" model is intended to ensure that we can continuously provide high-quality product updates and technical support, ensuring long-term stable system operation rather than stopping service after one-time delivery.

Q: What is the upgrade mechanism for later qData versions?

A: qData upgrade service is divided into two stages: free period and subscription period:

  • Free upgrade period (first year)
    Both source code authorization and installation package authorization include one year of free upgrade service. During the validity period, you can upgrade the system to the latest released version at any time.

    We recommend following the "Qiantong Tech" WeChat official account to receive new version release notices in time.

  • Subscription upgrade period (after one year)
    After the one-year period expires, if you need to continue receiving new version features and security updates, you need to purchase the annual subscription upgrade service (please refer to the quotation sheet for specific pricing).

  • If not renewed
    If you do not renew after expiration, you can still use the currently installed version permanently for free, but you will not be able to obtain subsequent new version upgrade services.

Q: What cooperation models are supported?

A: We provide flexible and diverse cooperation models to meet the needs of different business scenarios:

  • Authorization and development
    Supports independent use after purchasing authorization or secondary development.
  • Projects and services
    Provides overall outsourcing, on-demand custom development, professional consulting, and implementation deployment services.

Note: except for basic authorization, the above additional services such as customization, outsourcing, and consulting require separate fees. For specific fee standards, please refer to the latest quotation sheet or directly consult your customer manager.

Q: What deployment solutions does qData support?

A: qData provides flexible deployment solutions and fully adapts to various hardware architectures and operating systems, including Windows, Linux, and domestic operating systems:

  • Deployment modes

    • Single-node lightweight deployment: applicable to quick validation, test environments, or small business scenarios.
    • Multi-node cluster deployment: the recommended solution for production environments. By separating qData backend programs from computing engines, it effectively breaks through performance bottlenecks.

  • Function and performance notes
    Regardless of deployment method, product functions are completely consistent. The main difference lies in processing performance under high concurrency.

    Note: even in single-node deployment mode, qData can normally support scheduling computing engines with tens of thousands of nodes, meeting large-scale computing needs.

View"qData Performance Bottleneck Analysis and Tuning"

Q: Does qData support offline deployment?

**A: ** supports.

For intranet-isolated environments and Xinchuang scenarios, we provide a complete offline delivery solution:

  • Delivery form
    Provides a full set of native JAR packages and Docker offline images, allowing installation without internet access.
  • Architecture adaptation
    Offline images support both x86 and ARM architectures, perfectly adapting to various domestic hardware and operating system environments and meeting strict intranet deployment requirements.

View "qData Data Platform: Compatibility Notes for Full ARM Architecture and Xinchuang Domestic Environments"

Q: What kind of configuration is needed to run qData in a production environment?

It should be clear that qData, as a data platform, mainly undertakes scheduling and governance functions and does not directly execute massive computing itself. The true performance core lies in resource configuration of the underlying big data platform, such as Spark/Flink, and data warehouse model design. Therefore, configuration planning must consider:

  1. qData itself: configure application servers according to the number of management nodes and concurrent service requirements;
  2. Underlying computing cluster: independently plan computing and storage resources according to data throughput, task complexity, and storage strategy.

To help you scientifically plan overall resources, including the platform and underlying infrastructure, we have prepared detailed recommended configuration documents and performance notes. Please refer to:

View server resource configuration guide

View"qData Performance Bottleneck Analysis and Tuning"

Q: What types of servers and operating systems does qData support?

A: qData has broad hardware and system compatibility, does not depend on specific server brands, and fully supports Xinchuang environments.

  • Server architecture
    Supports standard x86 architecture servers and domestic servers based on ARM (aarch64) architecture, such as Huawei Kunpeng and Phytium.
  • Operating systems
    Perfectly adapts to mainstream Linux distributions and deeply supports various domestic operating systems, such as Kylin and UOS, meeting strict requirements for independent control among domestic government and enterprise customers.

View "qData Data Platform: Compatibility Notes for Full ARM Architecture and Xinchuang Domestic Environments"

Q: Is the demo environment data reset every day?

A: Yes. To keep the system clean and stable, data in the demo environment is automatically reset at 02:30 every morning.

If you need to use your own data for complete function validation, we provide a short-term private deployment service:

  • Service advantages: exclusive independent environment; data is not affected by resets.
  • Fee description: an agreement must be signed and corresponding fees paid. These fees can be fully deducted from a subsequent Pro Edition purchase.

If needed, please contact your customer manager for consultation and handling.

Q: Will training be provided after purchase? What if I am worried about difficulty getting started or insufficient after-sales support?

A: Please rest assured. We provide full-cycle training and after-sales assurance to ensure you can "buy with confidence and use smoothly".

To address customer concerns about onboarding difficulty and after-sales support, we provide a personalized implementation plan:

  • Diverse training formats: provides detailed operation documents, HD video tutorials, and expert one-on-one guidance, flexibly adapting to different learning preferences.
  • Deep content coverage: teaches not only tool operation, but also deeply conveys basic concepts, system development, and design philosophy, helping your team move from "able to use" to "using well".
  • Continuous after-sales companionship: training is only the beginning of service. We will continue to provide technical support to ensure problems encountered in later use receive timely responses and solutions.

Our goal is not only to deliver the product, but also to ensure your team can independently and efficiently operate the system.

Q: What after-sales technical support services do you provide? How are complex problems solved?

A: During the system subscription period, we provide continuous and free professional technical support to fully ensure stable system operation:

  • Core service content: covers architecture and function technical consulting, environment deployment guidance, daily usage guidance, and system bug fixes.
  • Tiered response mechanism:
    • Routine issues: you can submit them through the ticket system, and a dedicated team will quickly follow up and handle them.
    • Complex problems: for difficult technical scenarios, we will directly arrange senior technical consultants to provide remote online guidance, ensuring problems are deeply resolved.

We promise that "everything receives a response and every issue has follow-through", so you can use the system later without worries.

Q: Are there product introduction documents?

A: Yes. We provide a complete product documentation and business support system, covering the full project lifecycle:

  • Technical and product documents: include product manuals, user manuals, development/deployment documents, feature lists, detailed platform/system/technical architecture explanations, middleware and database adaptation notes, and more.
  • Solutions and promotional materials: provides white papers, product brochures, demo PPTs, business and sales solutions, construction blueprints, and more.
  • Full-process business support: supporting bidding documents, bid/preliminary design/feasibility study solutions, reporting materials, implementation packages, and industry solutions help you efficiently advance every stage from pre-sales, project initiation, bidding, construction, and implementation to promotion.

Q: Can you explain and demonstrate the system for us?

A: Yes. To give you the most efficient communication experience, we recommend the model of "review materials first, then schedule a meeting":

  1. Understand first: you can first review the product information package and full-process demo video we provide, which include detailed system introductions and core function demonstrations.
  2. In-depth communication: after you have an initial understanding of the product, you can contact your customer manager to schedule an online communication meeting. We will then discuss usage details, business scope, and targeted Q&A based on your specific needs.

This step-by-step approach avoids unfocused communication and ensures meeting time focuses on solving your core questions, greatly improving communication efficiency.

Q: Can we schedule a business discussion?

A: You are welcome to contact our customer manager at any time to schedule a business discussion.

To improve communication efficiency, we recommend that you first review the product information package and system demo video, focusing on key information such as the feature list, quotation sheet, and sales contract. After forming a basic understanding of the business terms and product overview, face-to-face or online in-depth discussions can match your needs more accurately and produce better communication results.

Q: Can you visit our company for on-site communication?

A: We are honored to receive your invitation and look forward to efficient face-to-face communication with your organization.

To maximize visit effectiveness, we recommend proceeding step by step:

  1. Preparation: please first review the product information package and system demo video, focusing on the feature list, quotation sheet, and sales contract to build a basic understanding of the product and business terms.
  2. Online warm-up: both parties can first arrange an online meeting for initial alignment and Q&A.
  3. On-site visit: after an initial cooperation intention is reached, we will immediately arrange a team to visit your company for in-depth communication.

This process ensures on-site communication focuses on core decisions and avoids spending time on basic introductions, improving overall cooperation efficiency.

Q: Can you cooperate with customers on pre-sales work, such as helping demonstrate and communicate with a third party?

A: Yes. As your partner with shared interests, we are very willing to assist you with pre-sales work and achieve a win-win result.

  1. Full-lifecycle document support: we provide a business support documentation system covering the full lifecycle of pre-sales, project initiation, bidding, construction, implementation, reporting, and promotion. This helps you efficiently complete internal project approval, external bidding, solution reporting, and project advancement, ensuring professional and standardized reporting to supervising departments and end users.
  2. On-site demo support: we also provide services to cooperate with you in on-site or face-to-face demonstrations and communication with third parties.
    • Note: this type of on-site accompaniment service is a value-added service. For specific needs, please directly contact your customer manager to discuss the detailed plan.

Q: Do you provide bidding support services?

A: Yes. We provide a business support documentation system covering the full lifecycle of pre-sales, project initiation, bidding, construction, implementation, reporting, and promotion.

  • Standard support: helps you efficiently complete internal project approval, external bidding, solution reporting, and project advancement, ensuring professional and standardized results reporting to supervising departments and end users.
  • Value-added services: deep customization needs such as writing bidding documents or bid proposals on your behalf belong to our value-added services. If needed, please contact your customer manager to discuss the specific support plan.

Q: Through which channels are pre-sales questions answered?

A: Please add our Enterprise WeChat, and you will receive dedicated service support:

  1. Daily consultation: directly contact your dedicated customer manager on WeChat for immediate answers.
  2. In-depth communication: if you need more professional support, you can schedule a phone meeting or online communication with a solution expert.

💡 Friendly reminder:
To improve communication efficiency, we recommend that you first review the product information package and system demo video, focusing on the feature list, quotation sheet, and sales contract. After you have a basic understanding of the product and business terms, further communication can resolve your core concerns more quickly.

A: Yes. To meet demonstration needs in different scenarios, we provide the following two environment options:

  1. Online shared demo environment
    You can reserve our online private demo environment.

    • Reservation mechanism: reservations are required according to resource scheduling, and queues may occur during peak periods.
    • Data note: the environment contains standard demo data and automatically rolls back every early morning, so personalized edits or persistent data cannot be retained.

  2. Short-term private deployment service
    If you need to customize the Logo, copyright information, and demo data yourself, we recommend this option.

    • Flexible customization: supports fully independent configuration and perfectly fits third-party demo needs.
    • Application note: this service involves independent resource deployment. For the specific application process, agreement, and details, please contact your customer manager for detailed consultation.

If needed, please contact your customer manager for detailed consultation and application. Click here to contact your customer manager

Q: Is there a private test environment where we can freely try, test, and validate functions using our own data sources?

A: Yes. We provide a short-term private deployment service, supporting deployment of a complete Pro Edition system on your organization's intranet servers.

  • Independent validation: you can conduct fully independent and controllable trials, tests, and function validation based on real data sources.
  • Flexible customization: supports fully independent configuration and perfectly fits third-party demo needs.
  • Application note: this service involves independent resource deployment. For the specific application process, agreement, and details, please contact your customer manager for detailed consultation.

If needed, please contact your customer manager for detailed consultation and application. Click here to contact your customer manager

Q: What is the technical livestream for? Are recordings available?

A: The technical livestream is an official recurring technical sharing program launched by Qiantong Tech. It is designed to visually demonstrate implementation methods for qData Data Platform, qKnow Knowledge Platform, and enterprise-grade AI.

  • Livestream time: every Thursday 16:00-17:00
  • Replay channel: missed the livestream? Visit the official Douyin account to watch the full replay.

Livestream content focuses on "implementable, operable, and replicable":

  • Product open classes: demos of core products such as qData Data Platform, qKnow Knowledge Platform, and qModel Algorithm Model Platform.
  • Technical practice: open-source technology sharing and new version release interpretation.
  • Case insights: real project case analysis and industry experience.
  • Interactive Q&A: online answers to technical problems and solution consulting.

Through livestreams, we hope to help you understand the product, master methods, and understand the industry, while establishing a direct communication channel and jointly accumulating long-term knowledge assets.

Q: Where can I see system update notices and detailed information?

A: The product is updated every 1-2 weeks. You can obtain version update notices and detailed information through the following channels:

Q: Can you help check whether our company or other subsidiaries have purchased before?

A: Yes. To ensure information security, please apply through the following process:

  1. Submit application: please provide an inquiry application letter stamped with your company's official seal.
  2. Contact channel: submit the application letter to your dedicated customer manager.
  3. Inquiry feedback: after verification, we will help you query the relevant purchase records.

Q: Which city is your company in? If you are not in the customer's city, how do you ensure after-sales service?

A: Qiantong Tech is headquartered in Nanjing, with branches in Zhengzhou and Urumqi. For customers in other locations, we have built a service system of "deep remote support + on-site fallback" to ensure service quality is not reduced:

1. Standard technical support (free during subscription)

We provide not only simple Q&A, but also full-cycle implementation assurance to ensure you can "use it and use it well":

  • Deep training and enablement: provides detailed operation documents, HD video tutorials, and optional expert one-on-one guidance, deeply conveying system design philosophy and development specifications.
  • Efficient response mechanism: for daily technical consulting, deployment guidance, and bug fixes, a dedicated team follows up throughout the process, breaking geographical limits and ensuring timely problem resolution.

2. Advanced on-site service (optional paid)

If there are complex scenarios that must be solved on site, such as on-site implementation or custom development, we provide paid on-site services. Please consult your customer manager for specific plans and quotations.

Our principle is: wherever you are, you can receive professional, timely, and implementable technical assurance.

Q: Can we visit your company on site?

A: Thank you very much for your recognition. We sincerely invite you to visit us. To make the trip worthwhile and achieve the best communication results, we recommend preparing in the following ways:

  1. Preparation: we recommend that you first carefully review the product information package, including the feature list and quotation sheet, as well as the demo video, to build an initial understanding.
  2. Online pre-communication: schedule an online meeting first. After both parties reach an initial cooperation intention, an on-site visit will be more effective.
  3. On-site visit: we support visits to the Nanjing headquarters or Zhengzhou branch.

For specific itinerary details, please consult your customer manager to make an appointment. Click here to contact your customer manager

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