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Leverage the Azure analytics platform's key analytics services to deliver unmatched intelligence for your data

Key Features

  • Learn to ingest, prepare, manage, and serve data for immediate business requirements
  • Bring enterprise data warehousing and big data analytics together to gain insights from your data
  • Develop end-to-end analytics solutions using Azure Synapse

Book Description

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.

What you will learn

  • Explore the necessary considerations for data ingestion and orchestration while building analytical pipelines
  • Understand pipelines and activities in Synapse pipelines and use them to construct end-to-end data-driven workflows
  • Query data using various coding languages on Azure Synapse
  • Focus on Synapse SQL and Synapse Spark
  • Manage and monitor resource utilization and query activity in Azure Synapse
  • Connect Power BI workspaces with Azure Synapse and create or modify reports directly from Synapse Studio
  • Create and manage IP firewall rules in Azure Synapse

Who this book is for

This book is for data architects, data scientists, data engineers, and business analysts who are looking to get up and running with the Azure Synapse Analytics platform. Basic knowledge of data warehousing will be beneficial to help you understand the concepts covered in this book more effectively.

Table of Contents

  1. Limitless Analytics with Azure Synapse
  2. Foreword
  3. Contributors
  4. About the author
  5. About the reviewer
  6. About the contributor
  7. Preface
    1. Who this book is for
    2. What this book covers
    3. To get the most out of this book
    4. Download the example code files
    5. Download the color images
    6. Conventions used
    7. Get in touch
    8. Reviews
  8. Section 1: The Basics and Key Concepts
  9. Chapter 1: Introduction to Azure Synapse
    1. Technical requirements
    2. Introducing the components of Azure Synapse
    3. Creating a Synapse workspace
    4. Understanding Azure Data Lake
    5. Exploring Synapse Studio
    6. Summary
  10. Chapter 2: Considerations for Your Compute Environment
    1. Technical requirements
    2. Introducing SQL Pool
    3. Creating a SQL pool
    4. Understanding Synapse SQL Pool architecture and components
    5. Examining DWUs
    6. Understanding distributions in Synapse SQL Pool
    7. Understanding partitions in Synapse SQL Pool
    8. Using temporary tables in Synapse SQL Pool
    9. Discovering the benefits of Synapse SQL Pool
    10. Understanding Synapse SQL on-demand
    11. SQL on-demand architecture and components
    12. Learning about the benefits of Synapse SQL on-demand
    13. Understanding Spark pool
    14. Spark pool architecture and components
    15. Creating a Synapse Spark pool
    16. Learning about the benefits of a Synapse Spark pool
    17. Summary
  11. Section 2: Data Ingestion and Orchestration
  12. Chapter 3: Bringing Your Data to Azure Synapse
    1. Technical requirements
    2. Using Synapse pipelines to import data
    3. Bringing data to your Synapse SQL pool using Copy Data tool
    4. Using Azure Data Factory to import data
    5. Using SQL Server Integration Services to import data
    6. Using a COPY statement to import data
    7. Loading data from a public storage account
    8. Loading data from a private storage account using an SAS token
    9. Using authentication mechanisms
    10. Summary
  13. Chapter 4: Using Synapse Pipelines to Orchestrate Your Data
    1. Technical requirements
    2. Introducing Synapse pipelines
    3. Integration runtime
    4. Activities
    5. Pipelines
    6. Triggers
    7. Creating linked services
    8. Defining source and target datasets
    9. Using various activities in Synapse pipelines
    10. Scheduling Synapse pipelines
    11. Creating pipelines using samples
    12. Summary
  14. Chapter 5: Using Synapse Link with Azure Cosmos DB
    1. Technical requirements
    2. Enabling the analytical store in Cosmos DB
    3. Data storage
    4. Transactional store
    5. Analytical store
    6. Querying the Cosmos DB analytical store
    7. Querying with Azure Synapse Spark
    8. Querying with Azure Synapse SQL Serverless
    9. Summary
  15. Section 3: Azure Synapse for Data Scientists and Business Analysts
  16. Chapter 6: Working with T-SQL in Azure Synapse
    1. Technical requirements
    2. Supporting T-SQL language elements in a Synapse SQL pool
    3. CTEs
    4. SELECT – OVER clause
    5. Using dynamic SQL in Synapse SQL
    6. Learning GROUP BY options in Synapse SQL
    7. Using T-SQL loops in Synapse SQL
    8. Creating stored procedures and views in Synapse SQL
    9. Stored procedures
    10. Views
    11. Optimizing transactions in Synapse SQL
    12. Supporting system views in a Synapse SQL pool
    13. Using T-SQL queries on semi-structured and unstructured data
    14. Reading Parquet files
    15. Reading JSON documents
    16. External tables
    17. Summary
  17. Chapter 7: Working with R, Python, Scala, .NET, and Spark SQL in Azure Synapse
    1. Technical requirements
    2. Using Azure Open Datasets
    3. Using sample scripts
    4. PySpark (Python)
    5. Spark (Scala)
    6. .NET Spark (C#)
    7. Spark SQL
    8. Summary
  18. Chapter 8: Integrating a Power BI Workspace with Azure Synapse
    1. Technical requirements
    2. Connecting to a Power BI workspace
    3. Creating your own dashboard on Azure Synapse
    4. Creating new Power BI datasets
    5. Creating Power BI reports
    6. Connecting Azure Synapse data to Power BI Desktop
    7. Connecting to a Synapse-dedicated SQL pool
    8. Connecting to a Synapse serverless SQL pool
    9. Summary
  19. Chapter 9: Perform Real-Time Analytics on Streaming Data
    1. Technical requirements
    2. Understanding various architecture and components
    3. Bringing data to Azure Synapse
    4. Using Azure Stream Analytics
    5. Using Azure Databricks
    6. Implementation of real-time analytics on streaming data
    7. Ingesting data to Cosmos DB
    8. Accessing data from the Azure Cosmos DB analytical store in Azure Synapse
    9. Loading data to a Spark DataFrame
    10. Creating visualizations
    11. Summary
  20. Chapter 10: Generate Powerful Insights on Azure Synapse Using Azure ML
    1. Technical requirements
    2. Preparing the environment
    3. Creating a Text Analytics resource in the Azure portal
    4. Creating an Anomaly Detector resource in the Azure portal
    5. Creating an Azure key vault
    6. Creating an Azure ML linked service in Azure Synapse
    7. Machine learning capabilities in Azure Synapse
    8. Data ingestion and orchestration
    9. Data preparation and exploration
    10. Training machine learning models
    11. Use cases with Cognitive Services
    12. Sentiment analysis
    13. Anomaly detection
    14. Summary
  21. Section 4: Best Practices
  22. Chapter 11: Performing Backup and Restore in Azure Synapse Analytics
    1. Technical requirements
    2. Creating restore points
    3. Automatic restore points
    4. User-defined restore points
    5. Geo-backups and disaster recovery
    6. Geo-redundant restore through the Azure portal
    7. Geo-redundant restore through PowerShell
    8. Cross-subscription restore
    9. Summary
  23. Chapter 12: Securing Data on Azure Synapse
    1. Implementing network security
    2. Managed workspace virtual network
    3. Private endpoint for SQL on-demand
    4. IP firewall rules
    5. SQL authorization
    6. Azure Active Directory authorization
    7. Implementing RBAC in a Synapse SQL pool
    8. Enabling threat protection
    9. Azure SQL auditing
    10. Azure Defender for SQL
    11. Understanding information protection
    12. Summary
  24. Chapter 13: Managing and Monitoring Synapse Workloads
    1. Technical requirements
    2. Managing Synapse resources
    3. Analytics pools
    4. External connections
    5. Integration
    6. Security
    7. Source control
    8. Monitoring Synapse workloads
    9. Integration
    10. Activities
    11. Analytics pools
    12. Managing maintenance schedules
    13. Creating alerts for Azure Synapse Analytics
    14. Summary
  25. Chapter 14: Coding Best Practices
    1. Technical requirements
    2. Implementing best practices for a Synapse dedicated SQL pool
    3. Maintaining statistics
    4. Using correct distribution for your tables
    5. Using partitioning
    6. Using an adequate column size
    7. Advantages of using a minimum transaction size
    8. Using PolyBase to load data
    9. Reorganizing and rebuilding indexes
    10. Materialized views
    11. Using an appropriate resource class
    12. Implementing best practices for a Synapse serverless SQL pool
    13. Selecting the region to create a serverless SQL pool
    14. Files for querying
    15. Using CETAS to enhance query performance
    16. Implementing best practices for a Synapse Spark pool
    17. Configuring the Auto-pause setting
    18. Enhancing Apache Spark performance
    19. Summary
    20. Why subscribe?
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