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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

The need for data democratization

Data democratization refers to the process of making data available to all relevant stakeholders to consume as is or add further value. This is critical for all businesses as it forces agile, data-driven decision making and helps them to remain competitive using actual metrics and data-centric strategies, as well as providing monetization and innovation opportunities. Let's take a look at a few concrete examples:

  • Healthcare and manufacturing: A new category of medical imaging device has been introduced into the market. A lot of vendors and hospitals buy these devices. The images, their quality, and their predictive power in aiding doctors to detect the onset of tumors and cancers based on certain positions and circumstances generate data points that need to be analyzed to see what positions and settings lead to the best diagnosis. The more data, the better the analysis and the quicker the feedback loop to provide to the manufacturer to...
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