Data cataloging is the process of obtaining a comprehensive inventory of digital assets. These assets include databases, data warehouses, data lakes, ERP systems, and CRM systems.

Data catalogs help users retrieve and analyze data. They can also provide a unified view of data assets within an organization.

Modern data catalogs are an essential component of data stewardship, curation, and data analytics. They are designed to provide democratic access to all data teams and data consumers.

The most recent generation of data catalogs, commonly referred to as Data Catalog 3.0, is a collaborative tool that helps employees uncover deeper insights, speed up decision-making, and optimize the lifecycle of BI Assets. It also promotes continuous development.

Today, the modern data catalog includes metadata and provides a standardized, granular view of a business’s data. Unlike previous generations, the new data catalogs are built on a knowledge graph. This allows the catalog to scan databases in a systematic manner.

Data profiling reviews the structure, content, and quality of a data source. It identifies any missing or invalid elements and flags issues. The results of this analysis can then be used to track the progress of a data set through the pipeline.

Automated data curation features use machine learning to identify data similarities, evaluate data fitness, and identify changes in the structure of data. These capabilities enable a data curator to effectively manage and share shared data.

Data owners play a crucial role in developing and maintaining a data catalog. These individuals ensure the quality of their data and collaborate with business users.