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Microsoft 365 and SharePoint Online Cookbook

You're reading from   Microsoft 365 and SharePoint Online Cookbook Over 100 practical recipes to help you get the most out of Office 365 and SharePoint Online

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781838646677
Length 810 pages
Edition 1st Edition
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Authors (2):
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Gaurav Mahajan Gaurav Mahajan
Author Profile Icon Gaurav Mahajan
Gaurav Mahajan
Sudeep Ghatak Sudeep Ghatak
Author Profile Icon Sudeep Ghatak
Sudeep Ghatak
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Toc

Table of Contents (19) Chapters Close

Preface 1. Section 1: AWS Data Engineering Concepts and Trends
2. Chapter 1: An Introduction to Data Engineering FREE CHAPTER 3. Chapter 2: Data Management Architectures for Analytics 4. Chapter 3: The AWS Data Engineer's Toolkit 5. Chapter 4: Data Cataloging, Security, and Governance 6. Section 2: Architecting and Implementing Data Lakes and Data Lake Houses
7. Chapter 5: Architecting Data Engineering Pipelines 8. Chapter 6: Ingesting Batch and Streaming Data 9. Chapter 7: Transforming Data to Optimize for Analytics 10. Chapter 8: Identifying and Enabling Data Consumers 11. Chapter 9: Loading Data into a Data Mart 12. Chapter 10: Orchestrating the Data Pipeline 13. Section 3: The Bigger Picture: Data Analytics, Data Visualization, and Machine Learning
14. Chapter 11: Ad Hoc Queries with Amazon Athena 15. Chapter 12: Visualizing Data with Amazon QuickSight 16. Chapter 13: Enabling Artificial Intelligence and Machine Learning 17. Chapter 14: Wrapping Up the First Part of Your Learning Journey 18. Other Books You May Enjoy

The benefits of the cloud when building big data analytic solutions

For a long time, organizations relied on complex systems that they would run in their own data centers to help them capture, store, and process large amounts of data. But over the last decade, there has been a trend of an increasing amount of data that organizations want to store and analyze, and on-premises systems have struggled to scale to keep up with demand. Scaling up these traditional tools for managing ever-increasing datasets has been expensive, complex, and time-consuming, and organizations have been seeking alternative solutions to cope with the increasing data volumes.

Ever since Amazon launched AWS in 2006, organizations have been realizing the benefits of running their workloads in the cloud. Cloud computing enables scalability, cost efficiency, security, and automation, which most companies find impossible to achieve within their own data centers, and this applies to the area of data analytics as well. One of the first AWS services was Amazon Simple Storage Service (Amazon S3), a cloud-based object store that offers essentially unlimited scalability at low cost, and yet provides durability and availability that most data center managers could only dream of achieving. Today, Amazon S3 has become the physical storage layer for thousands of data lake projects, and a wide ecosystem of analytic tools has been created to work with the service.

Successful data engineers need to understand the tools available in the cloud for building out complex data analytic projects and understand which set of tools is best to achieve the outcome needed for their project. In this book, you will learn more about AWS tools for working with big data, and you will gain hands-on experience in developing a data engineering pipeline in AWS.

To get started, you will either need an existing AWS account or you will need to create a new AWS account so that you can follow along with the practical examples. Follow along with the next section as we provide step-by-step instructions for creating a new AWS account.

You have been reading a chapter from
Microsoft 365 and SharePoint Online Cookbook
Published in: Jun 2020
Publisher: Packt
ISBN-13: 9781838646677
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