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

Adding data sources to your Power BI report

Before you publish your new report, let’s create additional data sources for it. This will allow us to build new reports later in Azure Synapse Studio.

The first report connected directly to your Data Explorer pool, and if configured to use the DirectQuery connectivity mode, could be used as a real-time report for telemetry. For the new data sources, we will connect to the lake database that we created in the Exploring Data Explorer pool data with Python section of Chapter 6, Data Analysis and Exploration with KQL and Python, and leverage the new columns we created as part of the data transformation process.

To create the new data sources, execute the following steps:

  1. In Power BI Desktop, click on Get data in the toolbar.
  2. In the Get Data window, pick Azure from the left-hand side of the window, and then select Azure Synapse Analytics SQL. Select Connect.
  3. You will see a dialog with the title SQL Server database...