Reader small image

You're reading from  Engineering Data Mesh in Azure Cloud

Product typeBook
Published inMar 2024
PublisherPackt
ISBN-139781805120780
Edition1st Edition
Concepts
Right arrow
Author (1)
Aniruddha Deswandikar
Aniruddha Deswandikar
author image
Aniruddha Deswandikar

Aniruddha Deswandikar holds a Bachelor's degree in Computer Engineering and is a seasoned Solutions Architect with over 30 years of industry experience as a developer, architect and technology strategist. His experience spans from start-ups to dotcoms to large enterprises. He has spent 18 years at Microsoft helping Microsoft customers build their next generation Applications and Data Analytics platforms. His experience across Application, Data and AI has helped him provide holistic guidance to companies large and small. Currently he is helping global enterprises set up their Enterprise-scale Analytical system using the Data Mesh Architecture. He is a Subject Matter Expert on Data Mesh in Microsoft and is currently helping multiple Microsoft Global Customers implement the Data Mesh architecture.
Read more about Aniruddha Deswandikar

Right arrow

Collecting and managing metadata

In the previous section, we looked at how data can be cataloged using Microsoft Purview. The built-in Microsoft Purview scanners scan and ingest basic technical metadata from data sources. This includes file types, column names, column types, and basic out-of-the-box classifications. However, this initial technical metadata is extracted from the data source purely based on the definitions available in the data source itself. Some data sources, such as Microsoft SQL Server, maintain significant amounts of data relating to the schema and its relationships. But others, such as CSV files stored in blob storage, do not have any information other than a column header. Hence, after the initial scan and ingest cycle, the governance team needs to get to work editing and enhancing the metadata to make the data assets more meaningful.

The real advantage of cataloging data and making it searchable is to make data more meaningful to the users. Users searching...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Engineering Data Mesh in Azure Cloud
Published in: Mar 2024Publisher: PacktISBN-13: 9781805120780

Author (1)

author image
Aniruddha Deswandikar

Aniruddha Deswandikar holds a Bachelor's degree in Computer Engineering and is a seasoned Solutions Architect with over 30 years of industry experience as a developer, architect and technology strategist. His experience spans from start-ups to dotcoms to large enterprises. He has spent 18 years at Microsoft helping Microsoft customers build their next generation Applications and Data Analytics platforms. His experience across Application, Data and AI has helped him provide holistic guidance to companies large and small. Currently he is helping global enterprises set up their Enterprise-scale Analytical system using the Data Mesh Architecture. He is a Subject Matter Expert on Data Mesh in Microsoft and is currently helping multiple Microsoft Global Customers implement the Data Mesh architecture.
Read more about Aniruddha Deswandikar