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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
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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

Delta helps address the inherent challenges of traditional data lakes and is the foundational piece of the Lakehouse paradigm, which makes it a clear choice in big data projects.

In this chapter, we examined the Delta protocol, its main features, contrasted the before and after scenarios, and concluded that not only do the features work out of the box but it is very easy to transition to Delta and start reaping the benefits instead of spending time, resources, and effort solving infrastructure problems over and over again.

There is great value when applying Delta to real-world big data use cases, especially those involving fine-grained updates and deletes as in the GDPR scenario, enforcing schema evolution, or going back in time using its time travel capabilities.

In the next chapter, we will look at examples of ETL pipelines involving both batch and streaming to see how Delta helps unify them to simplify not only creating but maintaining them.

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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