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.
4DAlert application can run on both cloud server as well as on unframed server. Our application can connect to could application which allows you to have fast and reliable data synchronization.
However, this platform also has some limitations. With on-premises storage, a malfunction in the system can cause you to lose your data. In this scenario, our solution allows you fully automate data reconciliation between multiple source systems and your analytics platform. It compares the source data with the target data and generates alerts when any record count mismatches or any anomaly is detected.
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