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Simplifying Data Engineering and Analytics with Delta

You're reading from   Simplifying Data Engineering and Analytics with Delta Create analytics-ready data that fuels artificial intelligence and business intelligence

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Product type Paperback
Published in Jul 2022
Publisher Packt
ISBN-13 9781801814867
Length 334 pages
Edition 1st Edition
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Author (1):
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Anindita Mahapatra Anindita Mahapatra
Author Profile Icon Anindita Mahapatra
Anindita Mahapatra
LinkedIn
Anindita Mahapatra is a lead 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 Think Big/Teradata, prior to which she was managing the development of algorithmic app discovery and promotion for both Nokia and Microsoft stores. She holds a master’s degree in liberal arts and management from Harvard Extension School, a master’s in computer science from Boston University, and a bachelor’s in computer science from BITS Pilani, India.
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Toc

Table of Contents (18) Chapters Close

Preface 1. Section 1 – Introduction to Delta Lake and Data Engineering Principles
2. Chapter 1: Introduction to Data Engineering FREE CHAPTER 3. Chapter 2: Data Modeling and ETL 4. Chapter 3: Delta – The Foundation Block for Big Data 5. Section 2 – End-to-End Process of Building Delta Pipelines
6. Chapter 4: Unifying Batch and Streaming with Delta 7. Chapter 5: Data Consolidation in Delta Lake 8. Chapter 6: Solving Common Data Pattern Scenarios with Delta 9. Chapter 7: Delta for Data Warehouse Use Cases 10. Chapter 8: Handling Atypical Data Scenarios with Delta 11. Chapter 9: Delta for Reproducible Machine Learning Pipelines 12. Chapter 10: Delta for Data Products and Services 13. Section 3 – Operationalizing and Productionalizing Delta Pipelines
14. Chapter 11: Operationalizing Data and ML Pipelines 15. Chapter 12: Optimizing Cost and Performance with Delta 16. Chapter 13: Managing Your Data Journey 17. Other Books You May Enjoy

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Authors (1)

Profile icon Anindita Mahapatra
Anindita Mahapatra
LinkedIn icon
Anindita Mahapatra is a lead 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 Think Big/Teradata, prior to which she was managing the development of algorithmic app discovery and promotion for both Nokia and Microsoft stores. She holds a master's degree in liberal arts and management from Harvard Extension School, a master's in computer science from Boston University, and a bachelor's in computer science from BITS Pilani, India.
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See other products by Anindita Mahapatra

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