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

Exploring additional ML capabilities in Azure Synapse

As we have seen, AutoML accelerates the adoption of ML in your existing analytics environment, especially if you are getting started with ML. It tests your data with different combinations of algorithms and parameters to find the model that offers the best result possible. However, if you’re an experienced ML engineer, there are other options available in Azure Synapse that will help you build your own projects while leveraging the parallel compute capabilities in Apache Spark and proximity with your Data Explorer pool data. Let’s briefly describe these options.

Using pre-trained models with Cognitive Services

Azure Cognitive Services is a cloud offering from Microsoft that provides APIs that developers can use to consume pre-trained artificial intelligence models in their applications. These pre-trained models facilitate building applications for computer vision, speech, language, and decision-making tasks....