When data is first loaded in the Discovery Center, certain analysis is run automatically, such as counting the number of data rows, measuring the maximum and minimum row length, and counting the number of duplicated rows. You can use business rules to create and run additional, business- and data-specific tests and tasks against your data at almost any step in the data profiling process.
Business rules are data expressions that are important for continued data management, data validation, exceptions handling, and error tracking. For some businesses, business rules assist in demonstrating legal compliance; for others, they help to implement routine business practices and optimize quality assurance.
In the Discovery Center, business rules have a name, unique ID (Sequence Number), priority, and an expression. Additionally, a rule can have a category, filter, group, and other elements. Each business rule is associated with a data source*. A data source (also described as an entity) represents a file in a directory or a table in a database. For more information, see Data Sources.
Finding Business Rules
The Discovery Center allows you to search for business rules (including library rules) as follows:
- Using the Find panel on the Home page
- Using advanced filters and conditions
- Using the search box available on the menu bar at the top of the Discovery Center. Enter the name of a business rule and click the search icon (
). All business rules matching the search text are listed in the Rules Search Results panel.
Managing Business Rules
Perform the following tasks to create, analyze, and manage the business rules in your repository:
Business Rules Library
The Business Rules Library is a centralized location where business rules are stored and shared. You create library rules by adding them to rule sets, which can then be exported for use across repositories by other Discovery Center users. For more information, see Business Rules Library.
* Rules stored in the Library are contained in rule sets. Rule sets may or may not be associated with a data source.