Reader small image

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

Product typeBook
Published inJul 2022
PublisherPackt
ISBN-139781801814867
Edition1st Edition
Concepts
Right arrow
Author (1)
Anindita Mahapatra
Anindita Mahapatra
author image
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

Right arrow

To get the most out of this book

Basic knowledge of SQL, Python programming, and Spark is required to get the most out of this book. Delta is open source and can be run both on-prem and in the cloud. Because of the rise in cloud data platforms, a lot of the descriptions and examples are in the context of cloud storage.

Use the following GitHub link for the Delta Lake documentation and quickstart guide to help you set up your environment and become familiar with the necessary APIs: https://github.com/delta-io/delta.

Databricks is the original creator of Delta, which was open sourced to the Linux Foundation and is supported by a large user community. Examples in this book cover some Databricks-specific features to provide a complete view of features and capabilities. Newer features continue to be ported from Databricks to open source Delta. Please refer to the proposed roadmap for the feature migration details: https://github.com/delta-io/delta/issues/920.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book's GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Simplifying Data Engineering and Analytics with Delta
Published in: Jul 2022Publisher: PacktISBN-13: 9781801814867

Author (1)

author image
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