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Scalable Data Analytics with Azure Data Explorer

You're reading from  Scalable Data Analytics with Azure Data Explorer

Product type Book
Published in Mar 2022
Publisher Packt
ISBN-13 9781801078542
Pages 364 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Jason Myerscough Jason Myerscough
Profile icon Jason Myerscough
LinkedIn
Jason Myerscough is a director of Site Reliability Engineering and cloud architect at Nuance Communications. He has been working with Azure daily since 2015. He has migrated his company's flagship product to Azure and designed the environment to be secure and scalable across 16 different Azure regions by applying cloud best practices and governance. He is currently certified as an Azure Administrator (AZ-103) and an Azure DevOps Expert (AZ-400). He holds a first-class bachelor's degree with honors in software engineering and a first class master’s degree in computing.
See other products by Jason Myerscough

Table of Contents (18) Chapters

Preface 1. Section 1: Introduction to Azure Data Explorer
2. Chapter 1: Introducing Azure Data Explorer 3. Chapter 2: Building Your Azure Data Explorer Environment 4. Chapter 3: Exploring the Azure Data Explorer UI 5. Section 2: Querying and Visualizing Your Data
6. Chapter 4: Ingesting Data in Azure Data Explorer 7. Chapter 5: Introducing the Kusto Query Language 8. Chapter 6: Introducing Time Series Analysis 9. Chapter 7: Identifying Patterns, Anomalies, and Trends in your Data 10. Chapter 8: Data Visualization with Azure Data Explorer and Power BI 11. Section 3: Advanced Azure Data Explorer Topics
12. Chapter 9: Monitoring and Troubleshooting Azure Data Explorer 13. Chapter 10: Azure Data Explorer Security 14. Chapter 11: Performance Tuning in Azure Data Explorer 15. Chapter 12: Cost Management in Azure Data Explorer 16. Chapter 13: Assessment 17. Other Books You May Enjoy

Ingesting data using one-click ingestion

In this section, we are going to learn how to ingest data using the Data Explorer Web UI and from an Azure Storage account using the one-click ingestion method.

Note

If you have not already cloned the Git repository, please do so now, so you can follow the example. The repository can be found here: https://github.com/PacktPublishing/Scalable-Data-Analytics-with-Azure-Data-Explorer.git.

Data ingestion is a three-step process:

  1. Ingestion Preparation: During the preparation phase, the table and mapping schemas are created.
  2. Ingestion: The file is then pulled from the queue, which is temporarily stored on an internal storage account, https://9qwkstrldmyerscoughadx01.blob.core.windows.net/20210614-ingestdata-e5c334ee145d4b43a3a2d3a96fbac1df-0/1623671437639_season-1819_csv.csv, and then ingested.
  3. Data Preview: Once the data has been ingested, it can be previewed and is ready for you to begin querying.

The following section...

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Authors (1)

Profile icon Jason Myerscough
LinkedIn
Jason Myerscough is a director of Site Reliability Engineering and cloud architect at Nuance Communications. He has been working with Azure daily since 2015. He has migrated his company's flagship product to Azure and designed the environment to be secure and scalable across 16 different Azure regions by applying cloud best practices and governance. He is currently certified as an Azure Administrator (AZ-103) and an Azure DevOps Expert (AZ-400). He holds a first-class bachelor's degree with honors in software engineering and a first class master’s degree in computing.
Read more
See other products by Jason Myerscough

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