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

Product typeBook
Published inJul 2022
PublisherPackt
ISBN-139781801814867
Edition1st Edition
Concepts
Big Data
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Author (1)
Anindita Mahapatra
Anindita Mahapatra
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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.
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Summary

In this chapter, we emphasized the need to choose the right architecture for future-proofing a business. This choice will determine the future agility of on-boarding use cases and the productivity of data personas in exploring and executing use cases. Traditional data warehouses and data lakes have their own strengths and weaknesses, and the lakehouse is a happy amalgamation of the two technologies.

The data format of warehouses is closed and proprietary, whereas a lakehouse prescribes an open data format. Our recommendation is to use Delta, as it is the best open source data format in the open source community today. The data type of warehouses caters to mostly structured data, and some semi-structured, whereas a lakehouse supports all kinds of data, including unstructured. Cloud storage is highly scalable, durable, and cost-effective, so a lakehouse is not only highly scalable but much cheaper and more performant than its warehouse counterpart. A warehouse was designed...

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Simplifying Data Engineering and Analytics with Delta
Published in: Jul 2022Publisher: PacktISBN-13: 9781801814867
© 2022 Packt Publishing Limited All Rights Reserved

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

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