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Data Lakehouse in Action

You're reading from Data Lakehouse in Action

Product type Book

Published in Mar 2022

Publisher Packt

ISBN-13 9781801815932

Pages 206 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Pradeep Menon

Table of Contents (14) Chapters

Preface

1. PART 1: Architectural Patterns for Analytics

2. Chapter 1: Introducing the Evolution of Data Analytics Patterns

3. Chapter 2: The Data Lakehouse Architecture Overview

4. PART 2: Data Lakehouse Component Deep Dive

5. Chapter 3: Ingesting and Processing Data in a Data Lakehouse

6. Chapter 4: Storing and Serving Data in a Data Lakehouse

7. Chapter 5: Deriving Insights from a Data Lakehouse

8. Chapter 6: Applying Data Governance in the Data Lakehouse

9. Chapter 7: Applying Data Security in a Data Lakehouse

10. PART 3: Implementing and Governing a Data Lakehouse

11. Chapter 8: Implementing a Data Lakehouse on Microsoft Azure

12. Chapter 9: Scaling the Data Lakehouse Architecture

13. Other Books You May Enjoy

Further reading

For more information regarding the topics that were covered in this chapter, take a look at the following resources:

Massively Parallel on Wikipedia: https: //en.wikipedia.org/wiki/Massively_parallel
Welcome to Azure Stream Analytics: https: //docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-introduction
Introduction to Stream Analytics windowing functions: https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions
HDFS Architecture Guide: https://hadoop.apache.org/docs/r1.2.1/hdfs_design.html
Evaluation of distributed stream processing frameworks for IoT applications in Smart Cities (2019), by Hamid Nasiri, Saeed Nasehi, and Maziar Goudarzi, in Journal of Big Data: https: //journalofbigdata.springeropen.com/articles/10.1186/s40537-019-0215-2
A Comparative Study on Streaming Frameworks for Big Data (2018,) by Wissem Inoubli, Sabeur Aridhi, Haithem Mezni, Mondher Maddouri, and Engelbert Mephu...

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Authors (1)

Pradeep Menon

Pradeep Menon is a seasoned data analytics professional with more than 18 years of experience in data and AI. Pradeep can balance business and technical aspects of any engagement and cross-pollinate complex concepts across many industries and scenarios. Currently, Pradeep works as a data and AI strategist at Microsoft. In this role, he is responsible for driving big data and AI adoption for Microsoft’s strategic customers across Asia. Pradeep is also a distinguished speaker and blogger and has given numerous keynotes on cloud technologies, data, and AI.

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