Supporting analytical applications in SQL Server differs quite a lot from supporting transactional applications. The typical schema for reporting queries is the star schema. In a star schema, there is one central table called a fact table and multiple surrounding tables called dimensions. The fact table is always on the many side of every relationship with every dimension. A database that supports analytical queries and uses the star schema design is called Data Warehouse (DW). Dealing with data warehousing design in detail is beyond the scope of this book. Nevertheless, there is a lot of literature available. For a quick start, you can read the data warehouse concepts MSDN blog at https://blogs.msdn.microsoft.com/syedab/2010/06/01/data-warehouse-concepts/. The WideWorldImportersDW demo database implements multiple star schemas. The following...
Mastering SQL Server 2017
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Mastering SQL Server 2017
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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
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Table of Contents (20 chapters)
Title Page
Copyright
About Packt
Preface
SQL Server Tools
JSON Support in SQL Server
Stretch Database
Temporal Tables
Columnstore Indexes
SSIS Setup
What Is New in SSIS 2016
Key Components of a Modern ETL Solution
Dealing with Data Quality
Unleash the Power of SSIS Script Task and Component
On-Premises and Azure Big Data Integration
Extending SSIS Custom Tasks and Transformations
Scale Out with SSIS 2017
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Customer Reviews