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Application Scenarios

Last updated: 2024-11-07 20:46:10
    As a universal data tool product, Tencent Cloud WeData has a very broad range of scenarios. The following explains some typical scenarios.

    Enterprise-level Data Warehouse Construction

    Tencent Cloud WeData provides complete data processing features, covering the full link of data warehouse construction. From importing data from heterogeneous data sources to supporting the entire process of data development, task orchestration, and task operations through the support of a variety of big data components, it standardizes the production of each layer and data domain of the data warehouse to ensure data standardization, integrity, and timeliness. Finally, by exporting data or via API services, the standardized data produced by the data warehouse is applied to various types of data businesses of the enterprise, empowering the business with data.
    
    
    

    Data Asset Governance

    Data assets are an important part of an enterprise's core assets and are the most core assets for data-driven companies. However, the inherent heterogeneity, complexity, and high costs of big data, along with the diversity and complexity of enterprise business, make the ready data processed from raw data exhibit problems such as poor quality, high costs, difficulty in understanding, and insecurity, preventing it from being directly used by the business as expected. Based on core data processing capabilities, Tencent Cloud WeData provides a series of data governance capabilities to help enterprises manage all aspects of data, enabling data to be confidently and boldly applied to business, efficiently creating value for business.
    
    
    

    Offline Data Warehouse/Data Platform Solution—Tencent Cloud WeData+EMR

    Based on data integration and development capabilities provided by Tencent Cloud WeData, it aggregates massive data from the business side. Then, leveraging EMR's powerful PB-level data computing and storage capabilities, it provides a high-performance enterprise-level offline data warehouse solution and can unify security management and data quality governance of the data warehouse through Tencent Cloud WeData, providing a unified, standardized data warehouse system to support users in further mining data value.
    
    
    

    Real-time Data Warehouse Solution—DataInLong/Oceanus+CDW

    On top of the massive parallel processing and OLAP analytical capabilities provided by cloud data warehouse CDW-PG/CK, real-time data processing is performed by Oceanus, helping users to quickly aggregate and collect data, and build a lightweight, low-cost, scalable real-time data warehouse. It can be paired with UDP for data catalog management. When further data governance capability is needed, Oceanus can be smoothly upgraded to Tencent Cloud WeData, providing further data processing, quality governance, and exploratory analysis capabilities.
    
    
    

    Fully Managed Data Lake Solution—DataInLong/Tencent Cloud WeData+DLC

    On top of the computation-storage separated massive big data analysis architecture provided by DLC, through DataInLong's real-time data ingestion and cleansing capabilities, it achieves unified aggregation of diverse heterogeneous data from the business side, building a low-cost, highly elastic, fully managed data lake solution. DataInLong can be smoothly upgraded to Tencent Cloud WeData, providing further data processing, quality governance, and exploratory analysis capabilities.
    
    
    

    Data Visualization Solution—Tencent Cloud WeData+BI

    Based on the data warehouse metric management and data service capabilities provided by Tencent Cloud WeData, connecting data to the "last mile" of business and coupling with BI's self-service report building and visual analysis capabilities, Tencent Cloud WeData provides a more convenient, simple, and intuitive way for users to work with data. At the same time, leveraging Tencent Cloud WeData's powerful data asset governance capability, Tencent Cloud WeData ensures the standardization, accuracy, and consistency of data, making data-assisted decision-making more reliable.
    
    
    
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