Here we discuss how CABAM can help you to clean, maintain and measure your master data quality. Master Data is critical.
It is what we use to drive our apps, to drive all the transactions and to make sure the rules are being applied correctly, but Master Data is also critical when it comes to reporting, analysis and correlations. It is critical that Master Data is clean and CABAM is here to help you identify where you’ve got Master Data issues and then to measure it, score it and keep it clean.
Here we will demonstrate how CABAM uses Record Completeness to discover whether all the fields within a particular record have been completed adequately by ensuring that a specified group of fields is fully populated or identifying nulls in a group of mandatory fields. This is to avoid incomplete records that cause errors in downstream processes or […]
In this function, we will demonstrate how CABAM can use the Master Data Completeness Function to compare 2 different fields from 2 different tables in order to find matching values or percentages of matching values. This may be done to avoid reporting issues pr operational delays arising from non-standardised data. Let’s say – for […]
In this function, we will demonstrate how CABAM can be used to identify scenarios where you have transactional data without the corresponding master data or to find slave data records that are redundant and need to be flagged as inactive or deleted. This is to avoid reports being distorted, possibly leading to an incorrect […]