Book Image

Limitless Analytics with Azure Synapse

By : Prashant Kumar Mishra
Book Image

Limitless Analytics with Azure Synapse

By: 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)
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

Introducing SQL Pool

SQL Pool uses a scale-out, node-based architecture with one control node and multiple compute nodes for distributed computational processing. Control nodes are a single point of contact for end users to interact with all compute nodes. The control node runs the Massively Parallel Processing (MPP) engine, which passes an operation to multiple compute nodes to do their work in parallel. MPP databases are optimized for analytical workloads, such as aggregating and processing large datasets. In this type of architecture, each compute node (which are also called processing units) works independently, with its own operating system and dedicated memory.

In this section, you will learn about the architecture of SQL Pool, which will help you in understanding data distribution across various nodes in SQL Pool. We will cover how to create a SQL pool using both the Azure portal and Synapse Studio in the following section.

Creating a SQL pool

In this section, you will...