After you process the rpt_user_info_d table by generating retroactive data, you can create a dashboard in Quick BI to display the profiles of website users. This visualize the data in the rpt_user_info_d table.

Prerequisites

The data is processed. For more information, see Process data. The Quick BI console is opened and you have logged on to the console.

Background information

The rpt_user_info_d table contains fields such as region, device, gender, age, and zodiac. You can display core metrics, periodic changes, regional distribution, age and zodiac distribution, and records of users on a dashboard. If you want to view data changes over time, we recommend that you generate retroactive data of at least one week.

Procedure

  1. In the Quick BI console, click Default Workspace to go to the default workspace. You can also click Personal Workspace to go to your personal workspace.
  2. On the page that appears, click Data Sources in the left-side navigation pane. On the Data Sources page, click Create Data Source in the upper-right corner. In the Add Data Source dialog box, select MaxCompute on the Cloud Data Sources tab.
  3. In the Add MaxCompute Database dialog box that appears, enter a display name for the MaxCompute data source, the name of your MaxCompute project, and your AcessKey ID and AcessKey secret. Use the default value for the database endpoint. For more information about the database endpoint, see Configure endpoints.
    Click Test Connection. After The data source can be connected. appears, click Add.
  4. On the page that appears, find the rpt_user_info_d table and click the Create Dataset icon in the Actions column.
    In the Create Dataset dialog box that appears, enter the dataset name, select a location to store the dataset, and then click OK.
  5. On the Datasets page that appears, click the created dataset to edit the dataset.
    Common dataset processing procedures include changing dimensions and measures, changing the dimension type, adding calculated fields, creating hierarchies, changing the data type of a field, modifying the aggregate mode of measures, and creating association models.
  6. Change the dimension types of relevant fields. After changing the dimension types of fields, you can filter data based on the field values.
    1. Change the dimension type of the dt field.
      Right-click dt in the left-side navigation pane and choose Change Dimension Type > Date/Time (Source Format) > yyyyMMdd.
    2. Change the dimension type of the region field.
      Right-click region in the left-side navigation pane and choose Change Dimension Type > Geo > State/Province/Municipality. After you change the dimension type of the region field, a location icon appears before the field in the left-side navigation pane.
  7. Create a dashboard.
    You can create a dashboard to display the latest data as the data changes. To create a dashboard, determine the display content, layout, and style, create charts, and associate charts to enable filter interaction.
    1. On the Datasets page, find the rpt_user dataset and click the Create Dashboard icon in the Actions column. On the page that appears, select Standard. The dashboard editing page appears.
    2. On the Data tab on the right, drag a kanban from the dataset selection section to the dashboard configuration section.
      In the dataset selection section, select the rpt_user dataset from the drop-down list at the top and drag pv to the dashboard configuration section.

      The rpt_user_info_d table is a partitioned table. Therefore, you must select a dimension under dt, drag it to the Filters section, click the Filter icon next to the dimension, and then specify a time period in the Set Filter dialog box. In this example, the specified time period is 2019 to 2019. Then click Update at the bottom of the dashboard configuration section.

    3. Create a trend chart. Drag the Line Chart icon at the top to the chart section on the left.
      Set parameters in the dashboard configuration section on the right and click Update.
      • Value Axis (Mea.): Set the value to pv.
      • Category Axis (Dim.): Set the value to dt(day).
      • Color Legend (Dim.): Set the value to age_range.
      • Filters: Set the value to dt(year).
    4. Create a geo map. Click the Color map icon at the top. In the dataset selection section on the right, select the rpt_user dataset from the drop-down list. In the chart configuration section, set Geo Location (Dim.) to region, Colorscale (Mea.) to pv, and Filters to dt(day), and click Update.
    5. Click Save and Preview in the upper-right corner in sequence to view the trend chart and geo map.