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

Data storage

A Cosmos DB analytical store is fully isolated from transactional workloads. The operational data in a Cosmos DB container is internally stored in row-based transactional stores in order to allow fast transactional reads and writes.

It is not recommended to run complex queries on your transactional workload – it may cause bad performance for your application running these queries. Ideally, you should add an analytical data layer on top of Cosmos DB transactional data if you want to perform complex operations on the data. The major caveat for this architecture is an ETL operation for data sync between transactional and analytical data stores. This additional step may lead to increased Total Cost of Operation (TCO) and overhead of maintaining the data in sync always.

With this new feature of Synapse Link, Cosmos DB gives you the flexibility to enable an analytical store within your Cosmos DB account without performing an ETL operation. Both the data layers are...