Mastering Azure Synapse Analytics

Cloud analytics is a crucial aspect of any digital transformation initiative, and the capabilities of the Azure Synapse analytics platform can simplify and streamline this process. By mastering Azure Synapse Analytics, analytics developers across organizations can boost their productivity by utilizing low-code, no-code, and traditional code-based analytics frameworks.

This book starts with a comprehensive introduction to Azure Synapse Analytics and its limitless cloud-scale analytics capabilities. You will then learn how to explore and work with data warehousing features in Azure Synapse. Moving on, the book will guide you on how to effectively use Synapse Spark for data engineering and data science. It will help you learn how to gain insights from your data through Observational analytics using Synapse Data Explorer. You will also discover the seamless data integration capabilities of Synapse Pipeline, and delve into the benefits of Synapse Analytics low-code and no-code pipeline development features. Lastly the book will show you how to create network topology and implement industry-specific architecture patterns in Azure Synapse Analytics.

By the end of the book, you will be able to process and analyze vast amounts of data in real-time to gain insights quickly and make informed decisions.

KEY FEATURES

* Explore the different features in the Azure Synapse Analytics workspace.
* Learn how to integrate Power BI and Data Governance capabilities with Azure Synapse Analytics.
* Accelerate your analytics journey with the no-code/low-code capabilities of Azure Synapse.

WHAT YOU WILL LEARN

* Leverage Synapse Spark for machine learning tasks.
* Use Synapse Data Explorer for telemetry analysis.
* Take advantage of Synapses common data model-based database templates.
* Query data using T-SQL, KQL, and Spark SQL within Synapse.
* Integrate Microsoft Purview with Synapse for enhanced data governance.

WHO THIS BOOK IS FOR

This book is designed for Cloud data engineers with prior experience in Azure cloud computing, as well as Chief Data Officers (CDOs) and Data professionals, who want to use this unified platform for data ingestion, data warehousing, and big data analytics.

1. Cloud Analytics Concept
2. Introduction to Azure Synapse Analytics
3. Modern Data Warehouse with the Synapse SQL Pool
4. Query as a Service- Synapse Serverless SQL
5. Synapse Spark Pool Capability
6. Synapse Spark and Data Science
7. Learning Synapse Data Explorer
8. Synapse Data Integration
9. Synapse Link for HTAP
10. Azure Synapse -Unified Analytics Service
11. Synapse Workspace Ecosystem Integration
12. Azure Synapse Network Topology
13. Industry Cloud Analytics

Debananda Ghosh is a Data and AI specialist and has been working in the Data and AI field for the past 17 years. His expertise includes, Data Warehouse, Database admin, Data Engineering, Big Data & AI, Data architecture, and related cloud analytics practice. Prior to Microsoft he was in Rolls Royce Singapore Data lab developing Aviation Analytics products in Cloud Big Data and AI platforms. He completed his bachelor’s in engineering from Jadavpur University, Kolkata, India, and a Post Graduate Program in Data Science and Business Analytics from McCombs School of Business at the University of Texas at Austin. He has worked with customers across multiple industries like finance, manufacturing, utilities, telecom, retail, e-commerce, and aviation. He is currently working with Microsoft cloud analytics products and helping industry partners achieve their digital transformation journey using advanced analytics and AI capability.

Debananda is also a distinguisher speaker, and blog writer, in cloud data and AI technology fields.