Book Image

Mastering SQL Server 2017

By : Miloš Radivojević, Dejan Sarka, William Durkin, Christian Cote, Matija Lah
Book Image

Mastering SQL Server 2017

By: Miloš Radivojević, Dejan Sarka, William Durkin, Christian Cote, Matija Lah

Overview of this book

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 Radivojevi?, Dejan Sarka, et. al SQL Server 2017 Integration Services Cookbook by Christian Cote, Dejan Sarka, et. al
Table of Contents (20 chapters)
Title Page
Free Chapter
1
Introduction to SQL Server 2017

Introduction

The 2016 release of SQL Server Integration Services is a major revision of the software. But, instead of being a complete re-write of the product, it's more an evolution of the product. Here is the SSIS timeline since its beginning in SQL Server 7.0 (1998):

In the early years of SQL Server, Microsoft introduced a tool to help developers and database administrators (DBA) to interact with the data: Data Transformation Services (DTS). The tool was very primitive compared to SSIS and it mostly relied on ActiveX and T-SQL to transform the data. SSIS V1.0 (2005) appeared in 2005. The tool was a game changer in the ETL world at the time. It was a professional and (pretty much) reliable tool for 2005. 2008/2008 R2 versions were much the same as 2005 in the sense that they didn't add much functionality, but they made the tool more scalable.

In 2012, Microsoft enhanced...