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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

Understanding and monitoring SLAs

A Service Level Agreement (SLA) is part of an explicit or implicit contract attesting to certain service quality metrics and expectations. Violation of some of these could result in penalties, fines, and loss of reputation. There is usually a cost and service quality tradeoff. So, it is important to articulate the SLA requirements of each use case and describe how it will be measured and tracked so that there is no ambiguity of whether it was honored or violated. There should also be clear guidance on how SLA violations are reported and the obligations and consequences on behalf of the service provider to remedy or compensate for the breach.

There are several types of SLA, and common ones include metrics for system availability, system response time, customer satisfaction as measured by Net Promoter Score (NPS), support tickets raised over a period of time, defect/error tickets and the response time to address them, and security incidents. It is...

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