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

Performing data ingestion

You have several options to load data into Azure Synapse Data Explorer. You can use one-click ingestion to quickly load some data and automatically create tables and data mappings as needed, with a few clicks of a mouse. For quick data exploration, you can use Kusto Query Language (KQL) commands to ingest data. If you have complex Azure Synapse pipelines or Azure Data Factory pipelines, you can use them for anything from robust data integration jobs to simple data movement tasks, leveraging rich logging, error handling, and more. Finally, if you need to build a custom application that connects to your Data Explorer pool using Data Explorer’s REST API for data ingestion, you can do that too.

The tool that you will use for data ingestion depends on your business needs and scenario. You can refer to the Running your first query section of Chapter 3, Exploring Azure Synapse Studio, where we already walked through the process to load data using the one...