Book Image

Learn Azure Synapse Data Explorer

By : Pericles (Peri) Rocha
Book Image

Learn Azure Synapse Data Explorer

By: Pericles (Peri) Rocha

Overview of this book

Large volumes of data are generated daily from applications, websites, IoT devices, and other free-text, semi-structured data sources. Azure Synapse Data Explorer helps you collect, store, and analyze such data, and work with other analytical engines, such as Apache Spark, to develop advanced data science projects and maximize the value you extract from data. This book offers a comprehensive view of Azure Synapse Data Explorer, exploring not only the core scenarios of Data Explorer but also how it integrates within Azure Synapse. From data ingestion to data visualization and advanced analytics, you’ll learn to take an end-to-end approach to maximize the value of unstructured data and drive powerful insights using data science capabilities. With real-world usage scenarios, you’ll discover how to identify key projects where Azure Synapse Data Explorer can help you achieve your business goals. Throughout the chapters, you'll also find out how to manage big data as part of a software as a service (SaaS) platform, as well as tune, secure, and serve data to end users. By the end of this book, you’ll have mastered the big data life cycle and you'll be able to implement advanced analytical scenarios from raw telemetry and log data.
Table of Contents (19 chapters)
1
Part 1 Introduction to Azure Synapse Data Explorer
6
Part 2 Working with Data
12
Part 3 Managing Azure Synapse Data Explorer

Understanding data export scenarios

As much as possible, when you are thinking about building your analytical environment, you should work with the premise of keeping a single point of truth in your data, meaning, you have one repository that holds the true version of your data. This is a structural principle of data management, especially in analytics, to ensure everyone makes decisions based on the same data. If someone needs to know how much product the company sold the previous month or the failure rate of IoT sensors, this one repository holds the truth that helps answer these questions. The moment you start copying data to different places, it becomes susceptible to user changes that affect a table’s layout, or even the data itself, creating several different versions of the data and removing that single point of truth.

However, not every analytical problem is solved in one single platform. The ability to export data to a different location is an essential tool in any...