You're reading from Simplifying Data Engineering and Analytics with Delta

Product typeBook

Published inJul 2022

PublisherPackt

ISBN-139781801814867

Edition1st Edition

Concepts

Big Data

Author (1)

Anindita Mahapatra

Section 1 – Introduction to Delta Lake and Data Engineering Principles

Understanding modern data architectures and sound data engineering principles and practices are crucial to ensure that your AI and BI strategies are reliable and defensible. Generated insights are going to be as good as the quality of the underlying data, so the upfront effort put into understanding the data, modeling it, and transforming it per the business needs goes a long way to foster innovation, productivity, and agility in your data teams.

This part includes the following chapters:

Chapter 1, An Introduction to Data Engineering
Chapter 2, Data Modeling and ETL
Chapter 3, Delta – The Foundation Block for Big Data

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Simplifying Data Engineering and Analytics with Delta

Published in: Jul 2022Publisher: PacktISBN-13: 9781801814867

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Author (1)

Anindita Mahapatra

Anindita Mahapatra is a Solutions Architect at Databricks in the data and AI space helping clients across all industry verticals reap value from their data infrastructure investments. She teaches a data engineering and analytics course at Harvard University as part of their extension school program. She has extensive big data and Hadoop consulting experience from Thinkbig/Teradata prior to which she was managing development of algorithmic app discovery and promotion for both Nokia and Microsoft AppStores. She holds a Masters degree in Liberal Arts and Management from Harvard Extension School, a Masters in Computer Science from Boston University and a Bachelors in Computer Science from BITS Pilani, India.
Read more about Anindita Mahapatra

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