Mastering SQL Server 2017: Build smart and efficient database applications for your organization with SQL Server 2017

Miloš Radivojević · Dejan Sarka · William Durkin · Christian Coté · Matija Lah

Aug 2019 · Packt Publishing Ltd

About this ebook

Leverage the power of SQL Server 2017 Integration Services to build data integration solutions with easeKey FeaturesWork with temporal tables to access information stored in a table at any timeGet familiar with the latest features in SQL Server 2017 Integration ServicesProgram and extend your packages to enhance their functionalityBook Description

Microsoft SQL Server 2017 uses the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. By learning how to use the features of SQL Server 2017 effectively, you can build scalable apps and easily perform data integration and transformation.

You’ll start by brushing up on the features of SQL Server 2017. This Learning Path will then demonstrate how you can use Query Store, columnstore indexes, and In-Memory OLTP in your apps. You'll also learn to integrate Python code in SQL Server and graph database implementations for development and testing. Next, you'll get up to speed with designing and building SQL Server Integration Services (SSIS) data warehouse packages using SQL server data tools. Toward the concluding chapters, you’ll discover how to develop SSIS packages designed to maintain a data warehouse using the data flow and other control flow tasks.

By the end of this Learning Path, you'll be equipped with the skills you need to design efficient, high-performance database applications with confidence.

This Learning Path includes content from the following Packt books:

SQL Server 2017 Developer's Guide by Miloš Radivojević, Dejan Sarka, et. al SQL Server 2017 Integration Services Cookbook by Christian Cote, Dejan Sarka, et. alWhat you will learnUse columnstore indexes to make storage and performance improvementsExtend database design solutions using temporal tablesExchange JSON data between applications and SQL ServerMigrate historical data to Microsoft Azure by using Stretch DatabaseDesign the architecture of a modern Extract, Transform, and Load (ETL) solutionImplement ETL solutions using Integration Services for both on-premise and Azure dataWho this book is for

This Learning Path is for database developers and solution architects looking to develop ETL solutions with SSIS, and explore the new features in SSIS 2017. Advanced analysis practitioners, business intelligence developers, and database consultants dealing with performance tuning will also find this book useful. Basic understanding of database concepts and T-SQL is required to get the best out of this Learning Path.

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About the author

Miloš Radivojević is a data platform MVP and specializes in SQL Server for application developers and performance/ query tuning. Miloš is a co-founder of PASS Austria. Dejan Sarka, MCT and Microsoft Data Platform MVP, is an independent trainer and consultant who focuses on the development of database and business intelligence applications. He is the founder of the Slovenian SQL Server and .NET Users Group. William Durkin is a data platform architect for Data Masterminds, he is a regular speaker at conferences around the globe, a Data Platform MVP, and the founder of the popular SQLGrillen event. Christian Coté is an MS-certified technical specialist in business intelligence (MCTS-BI). His ETL projects have used various ETL tools and plain code with various RDBMSes (such as Oracle and SQL Server). Matija Lah has more than 15 years of experience working with Microsoft SQL Server, mostly from architecting data-centric solutions in the legal domain.