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

Summary

As the usage of your Azure Synapse workspace grows, you may start to experience throttling errors at peak times due to extensive use of the compute resources in your Data Explorer pools. Having a plan to address resource usage through workgroup policies helps you better control the user experience and offer a balanced environment for all users. In addition to that, using techniques that help you speed up user queries helps you relieve stress on the platform, and resolve some requests more rapidly.

In this chapter, you learned how to implement resource governance to limit resource usage depending on who the user submitting the request is, the application that they are using, the description submitted with the request, and more. You learned how to create workload group policies, classify user requests to these policies, and enable the queueing of requests that are throttled for delayed execution.

You also learned how to pre-cache data to speed up queries. We explored the...