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
Stay in control of your data. Get notified on data issues before users use bad data to take wrong decisions.
Integrates with other systems within your landscape.
Integrated with SSO and compliant with security requirements.
Minimize risk, compliance and other data issues.
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