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.
March 26, 2020
As a growing company, we found in 4dalert’ expertise in data science invaluable. In almost two years of cooperation, they’ve helped us.
CI/CD Data Observability Data Quality Data Reconciliation
