What is Data Catalog? Importance of Data Catalog in Data Governance.
Data Catalog includes an inventory of data assets that is well organized in the Enterprise. Data Catalog uses metadata that will enable enterprises to well manage their data from time to time and It helps the data professionals or experts to collect, access, organize and enrich the concerned metadata which will support Data Governance.
A Data Catalog can be defined as a detailed inventory of all enterprise data assets in an enterprise, that is designed to help the data experts swiftly which will enable them to find the most accurate data which will serve all their business purposes.
Data Catalogs are one of the integral parts of modern data management and enterprises with that of Data Catalog are under the advantage as they can achieve the desired results with speed and agility and also it helps the professionals who want to perform Data Analysis.
Data Catalog includes data inventory, data management, searching, and data evaluation, however, it all depends on the capability in providing a collection of metadata. Data Catalog helps to make sound decisions by gaining control over data. It helps to collaborate the available data sources by enhancing data quality to gain a competitive edge.
The Purpose of the Data Catalog
Data Catalog enables you to understand both technical and business views of the data that is stored in the data sources. Data catalog centralizes and collaborates the information that is collected and which can be shared with the business functionality teams and Information Technology teams. Data Catalog includes many functions and features that depend on the capability of the cataloging data such as collecting metadata which helps to identify and describe the inventory of the data that is shareable.
Automated discovery of the datasets not only required for the constant discovery of new datasets but also for initial catalog build. To get the maximum value from the use of automation and also with the minimum manual effort, the use of Artificial Intelligence and Machine Learning for metadata collection, tagging, and semantic interference is vital.
Data Catalog can address the following challenges
- What kind of Data you have
- Who is responsible for moving it
- The purpose of the data
- Protection of the data
The ultimate aim of the Data Catalog is to pave the way for accessing the right data however let’s discuss the challenges of the Data catalog.
- Accessing the right data and prevent wastage of time
- To make a swift decision as per the business markets
Data Catalog offers
Data Search and Discovery – Data Catalog should have filtering and searching options that enable users to instantly find the relevant data that is needed for a plethora of Data management. It should also help users to enter any user-defined tags, technical information, or business terms which will help to improve the search functionalities. Capitalizing Metadata – Your data catalog helps to collect technical metadata from diverse connected data assets that include self-driving databases, on-premise systems, and object storage. Curation of Metadata – Data Catalog provides the subject matter or data experts to enable the knowledge in the form of enterprise tags, ratings, business glossary, classifications, annotations, etc. Automation – Artificial Intelligence and machine learning are often used to avoid manual tasks on the collected metadata. Furthermore, with the data, AI and machine learning can provide data recommendations regarding the data catalog users.
Features of Data Catalog
- Data Curation
- Data Usage Tracking
- Data lineage
- Business Glossary
- Collaborative Data Management
- Metadata Management
Benefits of a Data Catalog
- Helps in improving Data efficiency
- Saves time and money
- Helps in reducing dependencies
- Helps in reducing data risk and improving data culture
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