Azure Synapse Analytics Cookbook

Azure Synapse Analytics Cookbook

eBook Details:

  • Paperback: 238 pages
  • Publisher: WOW! eBook (April 29, 2022)
  • Language: English
  • ISBN-10: 1803231505
  • ISBN-13: 978-1803231501

eBook Description:

Azure Synapse Analytics Cookbook: Whether you’re an Azure veteran or just getting started, get the most out of your data with effective recipes for Azure Synapse

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.

  • Discover the optimal approach for loading and managing data
  • Work with notebooks for various tasks, including ML
  • Run real-time analytics using Azure Synapse Link for Cosmos DB
  • Perform exploratory data analytics using Apache Spark
  • Read and write DataFrames into Parquet files using PySpark
  • Create reports on various metrics for monitoring key KPIs
  • Combine Power BI and Serverless for distributed analysis
  • Enhance your Synapse analysis with data visualizations

By the end of this Azure Synapse Analytics Cookbook 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.

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