Configure Discovered Join Analysis - trillium_discovery - 17.1

The final step to adding a discovered join is configuring how you want the analysis to be run against the data. This includes specifying match quality, join complexity, and the types of values on which to join.

To configure and finish discovered join analysis

1. In the Create or Discover Joins window, click the Join tab. (See Creating and Discovering Joins.)
2. Keep the default Analysis Name or enter another name. By default, the Analysis Name field is populated as follows:

   Discover-Join-current date (YYYYMMDD). For example, if the current date is January 12, 2017, then the default analysis name would be Discover-Join-20170112.

3. Configure the following options:

   Option		Description
   Comparison Type
   Select one the following:
   	Value	Attempt to join on attribute values.
   	Metaphone	Attempt to join on attribute metaphone values.
   	Pattern	Attempt to join on attribute character pattern values. When selected, another drop-down list displays. Choose from the following character pattern types on which to compare the data: Default Greek Hebrew Long Rich Turkish For more information about patterns, see Character Patterns.
   	Mask	Attempt to join on attribute mask values.
   	Standardize - Integer	Attempt to join on values while ignoring leading zeroes. Example: Values 001 and 1 are considered a match.
   	Standardize - Decimal	Attempt to join on values and ignore leading and trailing zeroes. Example: Values 001.00, 1, and 1.00 are considered a match.
   	Standardize - String	Attempt to join on values while ignoring leading spaces, case, and any ASCII character other than A-Z, 0-9, +, or -. Example: Values blue (with leading and/or trailing spaces), blue, and, BLUE are considered a match.
   Complexity - Include inferred M:M joins		Select to discover all potential joins (including many to many relationships). If all attributes are selected for analysis, to ensure best performance this option is not recommended. Note: Inferred metadata is derived from the full volume of your data.
   Match Quality		Discovery Center finds potential joins greater than or equal to the value entered for Match Quality. This value corresponds to the Joins metadata column Match Best, the percentage match of the join (best match of values, LH rows, or RH rows). For example, to find all joins that match at least 90% of the time, enter a Match Quality of 90%.

4. Select Schedule job options:
   • Select Now (the default) to schedule the job to run when you click Finish.
   • Select Later to schedule the job to run at a later time. The current date and the time at the next half hour display. To change the date, click the calendar icon () and select a starting date. To change the time, click the clock icon () and select a time you want the job to run on the selected date.
5. Click Summary to review all selections and make edits as needed. Click Back or In Progress to return to the Join tab.
6. Do one of the following:
   • To add the join, click Finish. A message displays confirming the join analysis has been started or scheduled.
   • To close the window without saving your work, click Cancel or the X icon.
7. Do one of the following:
   • Click Add Another Join to continue adding joins. See Select Data Sources for Joins.
   • Click Task Manager to open the Task Manager and monitor the status of the join analysis job if run now. Scheduled tasks show a status of pending.
   • Click Done to close the window.

   To review join analysis results, see Viewing Join Metadata and Venn Diagrams.