This topic introduces the basic concepts, design philosophy, and scenarios of the data visualization feature of Data Management (DMS).

Background information

DMS allows you to manage databases and query data in the SQLConsole where results are returned in the form of a table. However, if you want to analyze business characteristics in scenarios such as trend analysis and growth comparison, tables cannot meet the requirements and data visualization is required. To resolve this issue, DMS provides the data visualization feature. You can use this feature to gain insights into your business and make better business decisions.


The data visualization feature provides a three-layer model for you to visualize data in various forms, including datasets, charts, and dashboards or big screens. You can execute SQL statements in the SQLConsole to obtain datasets and convert the datasets to common charts such as line charts, pie charts, column charts, circular charts, table charts, dual Y-axis charts, and funnel charts. Then, on a dashboard or big screen, you can freely combine and lay out these charts based on your analysis logic or methodology to visually present your business data.
Note For example, you can use indicator cards to display the overall metrics of your business, such as a transaction volume and unique visitors (UVs). Then, you can use a line chart to present the growth trend of the transaction volume and a column chart to compare transactions in all regions. Finally, you can use a table chart with a filter to query region-specific data.

Design philosophy

Two core concepts of data visualization are datasets and charts. Datasets are also called data views, and charts are also called visualization components.

  • Datasets represent the structured form of data. Data logic, permissions, and services are all based on this form.
  • Charts represent the visual form of data. Data presentation, interaction, and guidance are all based on this form.
    Note Datasets and charts complement each other to provide the same data in two different forms and help you better understand data.
  • Dashboards or big screens are used for quick data analysis and custom data visualization. You can combine charts on dashboards or big screens as needed. This can satisfy the data visualization needs of most users.


  • Analyze data in a secure and custom manner

    The data visualization feature is based on the security control feature in DMS. This ensures that data is authorized before it is visualized.

    • You can set the configurations only once to implement the advanced filtering, advanced control, interaction, drilling, download, and sharing of visual components. This facilitates data analysis and decision-making. For example, you can use this feature to compare data and analyze the geographic information of data, data distribution, data trends, and data clusters with ease.
    • Dashboards use automatic layouts. They can be used for most visual reports that require simple configuration and need to be viewed and shared with ease.
    • Big screens use custom layouts. They can be used for specific visual reports that require additional modifier elements and need to be retained for a long period of time. Time and efforts are required to configure a big screen in these scenarios, such as a big screen for massive online promotions.
  • Monitor operations in real time

    In the data factory of DMS, you can synchronize your business data in real time to AnalyticDB or ApsaraDB RDS where data can be analyzed. Then, you can visualize data that is analyzed in AnalyticDB or ApsaraDB RDS. This way, you can monitor database performance in real time and make sure that data flows are seamlessly connected. In addition, you can compare data to detect anomalies and handle key-link issues. Pivot-driven mode and chart-driven mode are provided for chart configuration. You can apply these modes to different scenarios based on your business requirements.