Analyzing data with SQL DI web UI

When training the model for an AI object, SQL Data Insights (SQL DI) collects key data statistics and renders them into metric scores for the model. The visualized scores can help you understand the results of AI queries on the object. You can view the data statistics and model scores on the Analyze data page of the SQL DI web UI.

Before you begin

Make sure that you have the authorization that is required for a specific task in SQL DI. See Managing SQL DI user permissions and Configuring setup user ID for SQL DI for details.

Procedure

  1. Sign in your SQL DI web UI with a valid RACF® user ID at the following address:


    https://<SQLDI-IPAddress>:<SQLDI-PortNumber>

    SQL DI uses a login group to identify and authorize users. The default group name is SQLDIGRP. Make sure that the user ID that you specify is defined in your SQL DI login group.

  2. On the Connections page, select a connection and click the Action selection menu action menu.
  3. Select List AI objects to open the AI objects page for the connection.
  4. Select an AI object and from the Action selection menu action menu, select Analyze data.
  5. On the Analyze data page, toggle between the Object details, Data statistics, Column influence, and Column discriminator tabs.
    • The Object details tab displays the column configuration information, including the name, Db2 data type, and SQL DI data type of a column.
    • The Data statistics tab displays the column value distribution information, including the most common value, the number of most common value, the number of unique value, standard deviation, mean, max, and min values of a column.
    • The Column influence tab, available after successful AI query enablement on the object, displays the column influence scores. An influence score correlates to the number of user-specified and SQL NULL values in a column and indicates the column's influence on the training of the object model. The fewer NULL values the column has, the higher influence score it generates.
    • The Column discriminator tab, available after successful AI query enablement on the object, displays the column discriminator scores. A discriminator score correlates to the number of unique values in a column and measures the column's ability to semantically distinguish its values from other values in the table. The more unique values the column has, the higher discriminator score it generates. The generally high discriminator score of the primary key column is not included on the tab because it may skew the representation of the scores of other columns.
  6. Click the Reload icon to reload the page to display data updates.