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Updated on 2022-12-16 GMT+08:00
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Application Scenario

Data Warehouse Migration

The data warehouse is an important data analytics system for enterprises. However, in this digital age, enterprises' own data warehouses fail to process the ever-growing service volumes due to their poor scalability and high costs. GaussDB(DWS) provides a good answer to these pain points. It is an enterprise-grade cloud data warehouse that boasts high performance, low cost, and smooth scale-out, helping enterprise data warehouses handle the growing data volumes at ease.

Figure 1 Data warehouse migration

Advantages

  • Seamless migration

    GaussDB(DWS) provides various migration tools to ensure the smooth migration of popular data analytics systems, such as Teradata, Oracle, MySQL, SQL Server, PostgreSQL, Greenplum, and Impala.

  • Compatibility with conventional data warehouses

    GaussDB(DWS) supports the SQL 2003 standard and stored procedures. It is compatible with some Oracle syntax and data structures, and can be seamlessly connected to common BI tools, saving service migration efforts.

  • Secure and reliable

    GaussDB(DWS) supports data encryption and connects to Database Security Service (DBSS) to ensure data security on the cloud. In addition, GaussDB(DWS) supports automatic full and incremental backup of data, improving data reliability.

Convergent Analysis of Big Data

Data has become the most important asset. Enterprises must be able to integrate their data resources and build big data platforms to mine the full value of their data. How to quickly mine values from massive data becomes a key factor for customers to implement predictive analysis.

Figure 2 Convergent analysis of big data

Advantages

  • Unified analysis entrance

    The GaussDB(DWS) SQL serves as the unified entrance of upper-layer applications, so that application developers can access all data using the SQL.

  • Real-time interactive analysis

    Analysis personnel can obtain immediately-actionable information from the big data platform in real time using broad analysis requests.

  • Auto scaling

    Adding nodes allows you to easily expand into PB-range capacity while enhancing query and analysis performance of the system.

Enhanced ETL + Real-Time BI Analysis

The data warehouse is the pillar of the BI system for collecting, storing, and analyzing massive volumes of data. It powers business decision analysis for the IoT, finance, education, mobile Internet, and Online to Offline (O2O) industries.

Advantages

  • Data migration

    Ability to import data in batches in real time from multiple data sources.

  • High Performance

    Cost-effective PB-level data storage and response to correlation analysis of trillions of data records within seconds.

  • Real-time processing

    Real-time consolidation of service data to produce actionable insights in operational decision-making.

Figure 3 Enhanced ETL + real-time BI analysis

Real-Time Data Analysis

In the mobile Internet and IoT domains, huge volumes of data must be processed and analyzed in real time to extract the full value from data. GaussDB(DWS) quickly imports and queries data and supports real-time data analysis using times series, stream, and AI engines.

Figure 4 Real-time data analysis

Advantages

  • Real-Time import of streaming data

    Data from IoT and Internet applications can be written into GaussDB(DWS) in real time after being processed by the stream computing and AI services.

  • Real-Time Monitoring and Prediction

    Device monitoring, control, optimization, supply, self-diagnosis, and self-healing based on data analysis and prediction.

  • Convergent AI analysis

    You can conduct association analysis on results of AI-based image and text data analysis and other service data on GaussDB(DWS).

  • IoT
    Figure 5 IoT

    GaussDB(DWS) helps you analyze massive amounts of data from Internet of Things (IoT) in real time and perform optimization based on the results. It is widely used in industrial IoT, O2O service system, and IoV solutions.

    Advantages of GaussDB(DWS) are as follows:

    • Real-time archiving of stream data: importing stream data from IoT devices and the gateway to GaussDB(DWS) using HUAWEI CLOUD DIS
    • Device monitoring and prediction: device monitoring, control, optimization, supply, self-diagnosis, and self-healing based on data analysis and prediction
    • Information recommendation: information recommended to users based on the data collected by their networked devices.
Parent topic: GaussDB(DWS)