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Limitless Analytics with Azure Synapse

Limitless Analytics with Azure Synapse

By : Saranya Ravichander, Prashant Kumar Mishra
4.6 (16)
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Limitless Analytics with Azure Synapse

Limitless Analytics with Azure Synapse

4.6 (16)
By: Saranya Ravichander, Prashant Kumar Mishra

Overview of this book

Azure Synapse Analytics, which Microsoft describes as the next evolution of Azure SQL Data Warehouse, is a limitless analytics service that brings enterprise data warehousing and big data analytics together. With this book, you'll learn how to discover insights from your data effectively using this platform. The book starts with an overview of Azure Synapse Analytics, its architecture, and how it can be used to improve business intelligence and machine learning capabilities. Next, you'll go on to choose and set up the correct environment for your business problem. You'll also learn a variety of ways to ingest data from various sources and orchestrate the data using transformation techniques offered by Azure Synapse. Later, you'll explore how to handle both relational and non-relational data using the SQL language. As you progress, you'll perform real-time streaming and execute data analysis operations on your data using various languages, before going on to apply ML techniques to derive accurate and granular insights from data. Finally, you'll discover how to protect sensitive data in real time by using security and privacy features. By the end of this Azure book, you'll be able to build end-to-end analytics solutions while focusing on data prep, data management, data warehousing, and AI tasks.
Table of Contents (20 chapters)
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1
Section 1: The Basics and Key Concepts
4
Section 2: Data Ingestion and Orchestration
8
Section 3: Azure Synapse for Data Scientists and Business Analysts
14
Section 4: Best Practices

Summary

In this chapter, we learned how to use different languages in a Synapse notebook to query data. Magic commands allow you to easily switch to any different language within the same notebook. We covered how to use Azure Open Datasets within a Synapse workspace. We also learned that a DataFrame or Spark table can be created using all the supported languages in Azure Synapse Analytics. In this chapter, we learned how to read data from Azure Data Lake Storage Gen2 accounts, how to create Spark DataFrames, and how to create Spark tables using PySpark, Scala, or .NET languages. We also covered how we can write data back to an Azure Data Lake Storage Gen2 account. Although we only covered Azure Data Lake Storage Gen2, we can use a similar approach for accessing data on blob containers.

So far, we have learned about using a Spark pool and SQL pool, and using different languages against these pools. However, our next area of focus will be the reporting tool.

In the next chapter...

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