• Integrated Data Quality– Perform the comprehensive data profiling statistics in context such as score cards, data domain interface, data quality rules and metric groups. This meta data will helps to understand the quality of data assets is the key feature in the Enterprise Data Catalog.
  • Semantic Search–Users can easily and rapidly find the relevant data with a single business term or column data without relying on IT Team and navigate the environment that they were familiar with.
  • End-to-end data lineage– Enterprise Data Catalog will track the data movement from source to destination with in-depth data lineage detail at a granular level.  This feature will help to get detailed impact analysis
  • Automated Data curation and notifications– Leverage AI powered Domain Discovery, Data Similarity and recommendations will help to reduce the manual work. The tool will have ability to send the automated notifications whenever the data assets underwent any changes.

Implementation and key findings for  Coleridge Initiative:

Coleridge Initiative took five weeks from start to finish to deploy the solution. As part of this assignment we have performed the environment setup, pre-installation tools, install Enterprise Data Catalog along with analyst tool.

The implementation included configuring the environment, Embedded cluster, secure configuration (SSL’s), LDAP authentication and building a custom metadata model (which they needed to meet their unique requirements), scan data from Microsoft SQL server data sources.