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
Practice in which incremental code changes are made frequently and reliably
Compare two database definitions and apply the differences from the source to the target
Collaborative data management practice
Flowchart that illustrates how “entities” such as people, objects or concepts relate to each other within a system.
Thought leader, trusted adviser, innovation coach and author in SAP intelligent technology and solutions. Business Leader with relentless optimism, technical and financial acumen and believes in building a bright future and a better world together. With a vision to innovate businesses, he works with leaders in multiple organizations to help drive digital transformation. Expert in SAP Cloud Platform, SAP intelligent technology and advanced analytics.
Speaker at SAP TechEd, Sapphire & S-KOM. Distinction of SAP Catalyst, SAP Executive Data Chef and SAP HANA Distinguished Engineer. Abani holds bachelor’s in Electrical Engineering from University College of Engineering, Odisha.
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