Reconcile data between source and analytics database after every data load
Measures how well a dataset meets criteria for accuracy, completeness, validity, consistency, uniqueness, timeliness, and fitness for purpose
Ability to understand, diagnose, and manage data health across multiple IT tools throughout the data lifecycle
An organized inventory of data assets in the organization
Flowchart that illustrates how “entities” such as people, objects or concepts relate to each other within a system.
Collaborative data management practice
Compare two database definitions and apply the differences from the source to the target
Practice in which incremental code changes are made frequently and reliably
Generate insights without worrying about data issues. Be aware of data issues ...
Better insights With Accurate Data. Be aware of data issues prior to ...
Build trust and confidence in data among end-users. Prevent data downtime by ...
Avoid Manual Data Reconciliation. Automated Pipeline or ETL Testing. Compare Schema and ...
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