In harmonization scenarios, it may happen that data from two entities need to be merged, even if there are problems joining them. Let's explore how you can use intelligent lookups for these scenarios.
Use of Intelligent Lookups
When combining data, there may be no column in your primary entity that contains data to uniquely identify a record in the other entity, and which would thus allow the creation of a standard join. Or, if such a column (a foreign key) exists, its data may be incomplete or unreliable. This can be particularly common when one of the entities comes from outside your organization. It may require a lot of manual work in spreadsheets to join the entities, and the results of this work may not be easy to reuse when new data arrives.
The intelligent lookup lets you iteratively join entities by defining rules to match records and then reviewing and processing the results.
You can use the following match strategies:
- Exact Match
- Fuzzy Match: fault-tolerant
These are the steps for creating an using an intelligent lookup:
- Create source objects (tables or views with key definition).
- Build the intelligent lookup: select source objects for data input and lookup and define the rules.
- Find matches: run or schedule the intelligent lookup, monitor the status and manually adjust matches if needed.
You need to run these rules, manually or scheduled. If the system does not find a match, or if it finds too many candidates, you can then add a different rule that is applied to this situation. Moreover, you can manually select the correct match which is then used in future for identical entries. You can integrate the result of an intelligent lookup in a view and use the view for another intelligent lookup.
