Updated on 2023-09-27 GMT+08:00

Step 7: DataArts Quality

DataArts Quality allows you to manage the quality of data in the databases. You can filter out unqualified data in a single column or across columns, rows, and tables from the following perspectives: integrity, validity, timeliness, consistency, accuracy, and uniqueness.

In the Data Quality module, the quality of metrics and data can be monitored.

Viewing Quality Jobs

After a job is executed during data development, you can view the running result of the job on the DataArts Quality page.

  1. Log in to the DataArts Studio console. Locate an instance and click Access. On the displayed page, locate a workspace and click DataArts Factory.

    Figure 1 DataArts Factory

  2. On the Develop Job page under DataArts Factory, open the job created in Step 6: DataArts Factory, and click the data quality monitor node in the job. In Node Properties, click next to Quality Rule Name to display the Quality Jobs page under DataArts Quality.

    Figure 2 Quality job node

  3. Click the name of a quality job to view its basic configuration.

    Figure 3 Quality job list

  4. In the left navigation pane, choose O&M. In the right pane, click Details in the Operation column to view the running result of the quality job.

    Figure 4 Running result of the quality job

Monitoring Business Metrics

The Metric Monitoring module manages business metrics.

To monitor a business metric, customize a SQL metric, define a rule based on the logical expression of the metric, and create and run a business scenario. Based on the running result of the business scenario, you can determine whether the business metric meets the quality rule. In this example, the system monitors the revenue of a taxi on a day and generates an alarm if the revenue is less than 500. The procedure is as follows:

  1. On the DataArts Studio console, locate an instance and click Access. On the displayed page, locate a workspace and click DataArts Quality.

    Figure 5 DataArts Quality

  2. Choose Metric Monitoring > Metrics from the left navigation bar.
  3. Click Create. In the displayed dialog box, set required parameters to create a metric.

    The SQL statement is as follows:

    SELECT SUM(fare_amount) FROM sdi_taxi_trip_data;
    Figure 6 Creating a metric

  4. Choose Metric Monitoring > Rule Management from the left navigation bar.
  5. Click Create. In the displayed dialog box, set required parameters to create a rule.

    Figure 7 Creating a rule

  6. Choose Metric Monitoring > Business Scenario Management from the left navigation bar.
  7. Click Create. In the displayed dialog box, set required parameters to create a scenario.

    Figure 8 Setting basic information
    Figure 9 Defining a rule group

    Click Next and select Once or On schedule for Repeat.

  8. In the scenario list, locate the created scenario and click Run in the Operation column.
  9. Click the execution result to view the monitored metric.

    Figure 10 Execution result

    The running result of the business scenario may be any of the following:

    • Normal: The instance stops normally and the running result meets the expectation.
    • Alarming: The instance stops normally, but the running result does not meet the expectation.
    • Abnormal: The instance stops unexpectedly.
    • --: The instance is running, but no running result is displayed.