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Data Lakehouse in Action

You're reading from Data Lakehouse in Action Architecting a modern and scalable data analytics platform

Product type Paperback

Published in Mar 2022

Publisher Packt

ISBN-13 9781801815932

Length 206 pages

Edition 1st Edition

Languages

Python

Tools

AWS IoT

Concepts

Big Data

Author (1):

Pradeep Menon

View More author details

Table of Contents (14) Chapters

Preface

1. PART 1: Architectural Patterns for Analytics

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

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

Discussing the themes of analytics capabilities

Data analytics is the process through which data is transformed into insights. Before getting into the technical components that enable this transformation, let's discuss themes of analytics capabilities that an organization requires. The analytical capabilities are targeted at two types of personas:

Technical users: Technical users are stakeholders with the technical skills to directly engage with the underlying data structures. They have skills in SQL, programming, data science, and data engineering. A typical technical user could be a data analyst, data engineer, data scientist, or data architect.
Functional users: Functional users are stakeholders with expertise in the specific functional domain, but their focus on technology is limited. They are subject matter experts, and they understand how the business or a particular domain functions. A typical functional user could be a business analyst or manager.

The...

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Authors (1)

Pradeep Menon

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.

See other products by Pradeep Menon

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