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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

Hands-on – reviewing reviews with Amazon Comprehend

Imagine that you work for a large hotel chain and have been tasked with developing a process for identifying negative reviews that have been posted on your website. This will help the customer service teams follow up with the customer.

If your company was getting hundreds of reviews every day, it would be time-consuming to have someone read the entire review every time a new review was posted. Luckily, you have recently heard about Amazon Comprehend, so you decide to develop a small Proof of Concept (PoC) test to see whether Amazon Comprehend can help.

If your PoC is successful, you will want to have a decoupled process that receives reviews once they have been posted, calls Amazon Comprehend to determine the sentiment of the review, and then takes a follow-up action if the review is negative or mixed. Therefore, you decide to build your PoC in the same way, using Amazon Simple Queue Service (SQS) to receive reviews...

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