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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
Languages
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Author (1):
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Anindita Mahapatra Anindita Mahapatra
Author Profile Icon Anindita Mahapatra
Anindita Mahapatra
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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

Data governance

Data democratization and self-service capabilities are some of the advantages of data lakes. A data governance layer is imperative to put the right guardrails in place while allowing stakeholders to get the most business value from the generated and curated data and insights. A good data catalog is essential for producing actionable insights in any data-driven organization. Cloud vendors have their own offerings, such as AWS Glue, Azure Purview, and Azure Data Catalog. Apache Atlas is probably the most popular open source offering, and there are vendors who specialize in this area such as Alation and Collibra.

The three primary goals of governance are the following:

  • Keeping data secure and only the right privileges and roles dictate access to data
  • Ensuring the quality of the stored data is high so that it is meaningful to its consumers, who then develop trust in their data and hence the insights generated on top of the data
  • Discovering data so that...
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