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Azure for Architects

You're reading from   Azure for Architects Implementing cloud design, DevOps, containers, IoT, and serverless solutions on your public cloud

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781789614503
Length 536 pages
Edition 2nd Edition
Tools
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Authors (2):
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Ritesh Modi Ritesh Modi
Author Profile Icon Ritesh Modi
Ritesh Modi
Daniel Andres Pelaez Lopez Daniel Andres Pelaez Lopez
Author Profile Icon Daniel Andres Pelaez Lopez
Daniel Andres Pelaez Lopez
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Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Azure Solution Availability and Scalability 3. Security and Monitoring 4. Cross-Subscription Deployments Using ARM Templates 5. ARM Templates - Modular Design and Implementation 6. Designing and Implementing Serverless Solutions 7. Azure Integration Solutions 8. Cost Management 9. Designing Policies, Locks, and Tags 10. Azure Solutions Using Azure Container Services 11. Azure DevOps 12. Azure OLTP Solutions Using Azure SQL Sharding, Pools, and Hybrid 13. Azure Big Data Solutions Using Azure Data Lake Storage and Data Factory 14. Azure Stream Analytics and Event Hubs 15. Designing IoT Solutions 16. Other Books You May Enjoy

ETL

A very popular process known as ETL helps in building a target data source to house data that is consumable by applications. Generally, the data is in a raw format, and to make it consumable, the data should go through the following three distinct phases:

  • Extract: During this phase, data is extracted from multiple places. There could be multiple sources and they all need to be connected to in order to retrieve the data. Extract phases typically use data connectors consisting of connection information related to the target data source. They might also have temporary storage to bring the data from the data source and store it for faster retrieval. This phase is responsible for the ingestion of data.
  • Transform: The data that is available after the extract phase might not be consumable directly by applications. This could be for a variety of reasons. The data might have irregularities...
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