Data catalogs have quickly become a core component of organizations that have been successful in garnering remarkable changes in the quality and speed of data analysis by modern data catalog implementations.

What is a Data Catalog?

Data Catalog combines data management, data inventory, searching, and data evaluation. It is a collection of metadata helping analysts and data users find the data that serves as an inventory of existing data. This data is needed to provide information to evaluate fitness data for intended uses.

In the age of big data and self-service analytics, data catalogs have accounted to be the standard for metadata management connecting the datasets with rich information to inform those people who work with data.

Depending on the core capability of cataloging data, a modern data catalog comes with a myriad of features and functions such as data searching, data evaluation, data access, and collection of the metadata that can identify and describe the inventory of shareable data. Maximum value can be extracted through AI and machine learning for metadata collection, tagging, and semantic inference, opening new doors to automation that would further minimize manual effort.

Data catalogs have an enormous impact on analysis activities, and a robust data catalog provides many other benefits such as improved data efficiency, reduced risk of error, improved data context, improved data analysis, intelligent dataset recommendations, data curation, data usage tracking, collaborative data management, and a variety of data governance features.

There’s no doubt that a data catalog is a key to an organization’s data sources, and here are a few challenges that can be addressed by implementing a data catalog in an organization.

Data Catalog to the rescue!

• Starts Agile Data Governance-Instead of deploying overly complex processes to begin with, data governance, a bottom-up approach can be taken into account wherein the starting point of your data governance would entail where your assets’ global knowledge should be. With this approach, it’s easier to maintain assumed information, and a connected data catalog enables organizations to do so, directly retrieving data from an enterprise’s.
• Accelerates Data Discovery- An abundance of information is generated each day as thousands of datasets and assets are being produced by organizations daily. Enterprises find themselves in deep trouble dealing with humongous information, understanding, and gaining insights from this information to create some value. 
• This is a cumbersome process, as a result of which data scientists are known to have spent 80% of their time in this process rather than analyzing and reporting their data. However, the deployment of a data catalog in an organization can speed up the data discovery process five times, letting data teams focus on what’s crucial for delivering their data projects within the deadline.
• Enables Metadata Management-Over time, a data catalog maintains a reliable and robust data asset landscape at the enterprise level enabling metadata synchronization with data sources and further enforcing documentation by data stewards, data owners, users, and so on.
• Builds Data Democracy-Since its interface does not require any technical expertise to understand the data, the information of data assets is not limited to a group of experts. Thus it becomes a reference data tool for all employees. It allows organizations to work on data assets in a simple way and better collaborate on those assets, building a powerful data democracy.

Summary

Data catalogs save the dedicated time your team spends on “data quarrels” activities and ensure reasonable control over data, simplifying data retrieval, intelligent decision-making, and the identification of knowers. Organizations can cross-reference data assets and quickly extract value from them to enable innovations that meet proven market needs.