IFS Data Catalog is to enable users to quickly find data assets within their IFS data sources so they can easily develop world class machine Learning Models (ML), Business Intelligence Analytics (BI), Business Automation Processes and highly-informative business reports. The data catalog will also help customers to contextualize the data found within large unstructured repositories of data such as those formed by the internet of thing (IoT). The catalog will also help customers govern their data by automatically classifying data and highlighting possible non-compliant data sources.
Data catalog is part of unified data governance where generate catalog of multiple data sources build a common catalog. Those data sources can be anything, from flat dat files, databases, and cloud storages.
The data catalog will be able to scan all IFS data sources, identifying, classifying, correlating, indexing, and registering data sets. The purpose of the Data Catalog is to:
- Scan the IFS data sources and create metadata catalog entries.
- Classify information within those data sources using the catalog Machine Learning (ML) and AI processes.
- Provide a consistent end-to-end view over entire IFS data estate.
- Allow to search and analyze data estate using the data catalog.
- Allow data stewards to get data insights out of overall data governance information base.
IFS will deliver a unique solution with the IFS Data Catalog. The catalog will be pre-loaded with existing metadata that describes the standard IFS Cloud Data Estate. The pre-loaded data will include commonly used IFS terminology and relationships. The catalog functionality for searching and browsing is accessible through the Aurena client user interface, which means the users can find the data within the same interface that modifies or consumes the data.