Book Image

Azure Synapse Analytics Cookbook

By : Gaurav Agarwal, Meenakshi Muralidharan
Book Image

Azure Synapse Analytics Cookbook

By: Gaurav Agarwal, Meenakshi Muralidharan

Overview of this book

As data warehouse management becomes increasingly integral to successful organizations, choosing and running the right solution is more important than ever. Microsoft Azure Synapse is an enterprise-grade, cloud-based data warehousing platform, and this book holds the key to using Synapse to its full potential. If you want the skills and confidence to create a robust enterprise analytical platform, this cookbook is a great place to start. You'll learn and execute enterprise-level deployments on medium-to-large data platforms. Using the step-by-step recipes and accompanying theory covered in this book, you'll understand how to integrate various services with Synapse to make it a robust solution for all your data needs. Whether you're new to Azure Synapse or just getting started, you'll find the instructions you need to solve any problem you may face, including using Azure services for data visualization as well as for artificial intelligence (AI) and machine learning (ML) solutions. By the end of this Azure book, you'll have the skills you need to implement an enterprise-grade analytical platform, enabling your organization to explore and manage heterogeneous data workloads and employ various data integration services to solve real-time industry problems.
Table of Contents (11 chapters)

Training a model using AutoML in Synapse

Azure Synapse Studio gives you the flexibility to develop a machine learning model on top of your dataset. In this recipe, you will learn how you can use the AutoML feature to train your model on the existing Spark tables. You can select the Spark table that you want to train the dataset on with the code-free experience of machine learning models using AutoML.

We will be using the regression model in this recipe. However, it is completely dependent on the problem that you are trying to solve, and you can choose from models including regression, classification, or Time Series Insights to fit your need.

Getting ready

We will be using the same Spark tables that we created in Chapter 2, Creating Robust Data Pipelines and Data Transformation.

We will need to do some setup to prepare for this recipe:

  • We need to do this to get ready for the next steps. For more on how to create the Azure Machine Learning workspace, you can refer...