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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

Managing and monitoring

Every organization has policies around data access and data use that need to be honored. In addition, there are compliance guidelines in some regulated industries to prove that compliance is honored, using an audit trail of the types of user access and manipulation of the data. Hence, there is a need to be able to set the controls in place, detect whether something has been changed, and provide a transparent audit trail. This includes access to raw data as well as via tables that are an artifact on top of the data.

The metrics collected from these logs need to be compared over a period of time to understand trend lines. Delta’s versioning capability comes in handy to monitor not only operations done on a table but metrics logged as well. It would be fair to say that these metrics need more permanence and some date/time stamp would be used to log them.

There are several types of logs in a system. The main ones include the following:

  1. Audit...
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