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

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Published inJul 2022
PublisherPackt
ISBN-139781801814867
Edition1st Edition
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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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Facilitating data sharing with Delta

JDBC/ODBC connections or HTTP connections via REST APIs are good for sharing modest data but may become a bottleneck for larger datasets. Consider the scenario of sharing curated data with external vendors or partners. There are some firms whose business model is centered around data sharing, such as S&P, Bloomberg, FactSet, Nasdaq, and SafeGraph. They aim to be the source of truth for financial datasets, which every other financial institution will be interested in consuming for downstream analysis and to augment their own datasets. Wouldn't it be nice not to have to copy the data multiple times?

It is best to use cloud storage access directly to avoid unnecessary platform-related bottlenecks. That is what Delta sharing attempts to do – provide an open standard to securely and seamlessly share large volumes of data in Parquet/Delta with a wide variety of consumers and an easy way to govern and audit. Consumers can be from pandas...

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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