Build smarter and efficient database application systems for your organization with SQL Server 2017Key Features<ul>
<li>Explore the development features of SQL Server 2017 to build database applications</li>
<li>Work with temporal tables to get information about data stored in a table at any point of time</li>
<li>Use adaptive querying to enhance the performance of your queries</li>
</ul>Book DescriptionMicrosoft SQL Server 2017 is a milestone in Microsoft's data platform timeline, as it integrates the power of R and Python for machine learning and containerization-based deployment on Windows and Linux.
This book starts with a quick introduction to the new features of SQL Server 2017 to help you get up and running with its latest features. You’ll be introduced to the enhancements in Transact-SQL and new database engine capabilities before advancing to JSON support. This guide will also take you through security improvements and enable you to work efficiently with temporal tables. You’ll then delve into advanced topics such as Query Store, columnstore indexes, and In-Memory OLTP. Toward the end of the book, you'll delve into R and discover how to use the R language with Transact-SQL for data exploration and analysis. You'll also learn how to integrate Python code into SQL Server, understand graph database implementations, and explore the flexibility of containers for development and testing.
By the end of this book, you’ll have learned how to design efficient high-performance database applications with SQL 2017 easily.What you will learn<ul>
<li>Explore the latest development features in SQL Server 2017</li>
<li>Identify opportunities for In-Memory OLTP technology</li>
<li>Use columnstore indexes for storage and performance improvements</li>
<li>Exchange JSON data between applications and SQL Server</li>
<li>Encrypt or mask data using new security features</li>
<li>Control access to data on row levels</li>
<li>Discover the potential of R and Python integration</li>
<li>Model complex relationships with graph databases in SQL Server 2017</li>
</ul>Who This Book Is ForDatabase developers and solution architects looking to design efficient database applications using SQL Server 2017 will find this book useful. Also, if you’re an advanced analysis practitioner, business intelligence developer, or a database consultant dealing with performance tuning, this book is for you.
Basic understanding of database concepts and T-SQL will assist with understanding key concepts covered in this book.Table of Contents<ol>
<li>Introduction to SQL Server 2017 9Introduction to SQL Server 2017</li>
<li>Review of SQL Server Features for Developers 23Review of SQL Server Features for Developers</li>
<li>SQL Server Tools 75SQL Server Tools</li>
<li>Transact-SQL and Database Engine Enhancements 115Transact-SQL and Database Engine Enhancements</li>
<li>JSON Support in SQL Server 187JSON Support in SQL Server</li>
<li>Stretch Database 241Stretch Database</li>
<li>Temporal Tables 289Temporal Tables</li>
<li>Tightening Security 353Tightening Security</li>
<li>Query Store 407Query Store</li>
<li>Columnstore Indexes 459Columnstore Indexes</li>
<li>Introducing SQL Server In-Memory OLTP 523Introducing SQL Server In-Memory OLTP</li>
<li>In-Memory OLTP Improvements in SQL Server 2017 557In-Memory OLTP Improvements in SQL Server 2017</li>
<li>Supporting R in SQL Server 593Supporting R in SQL Server</li>
<li>Data Exploration and Predictive Modeling with R 645Data Exploration and Predictive Modeling with R</li>
<li>Introducing Python 687Introducing Python</li>
<li>Graph Database 723Graph Database</li>
<li>Containers and SQL on Linux 767Containers and SQL on Linux</li>
</ol>

SQL Server 2017 Developer s Guide: A professional guide to designing and developing enterprise database applications

Computers & Technology

Sarka, Dejan

Radivojevic, Milos

Durkin, William

Programming

Packt Publishing

Leverage the power of SQL Server 2017 Integration Services to build data integration solutions with ease Key Features <ul>
<li>Work with temporal tables to access information stored in a table at any time </li> <li>Get familiar with the latest features in SQL Server 2017 Integration Services </li> <li>Program and extend your packages to enhance their functionality</li>
</ul> Book 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: <ul>
<li>SQL Server 2017 Developer's Guide by Milos Radivojevic, Dejan Sarka, et. al </li> <li>SQL Server 2017 Integration Services Cookbook by Christian Cote, Dejan Sarka, et. al</li> </ul> What you will learn <ul>
<li>Use columnstore indexes to make storage and performance improvements </li> <li>Extend database design solutions using temporal tables </li> <li>Exchange JSON data between applications and SQL Server </li> <li>Migrate historical data to Microsoft Azure by using Stretch Database </li> <li>Design the architecture of a modern Extract, Transform, and Load (ETL) solution </li> <li>Implement ETL solutions using Integration Services for both on-premise and Azure data</li>
</ul> Who 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.Table of Contents <ol>
<li>Introduction to SQL Server</li> <li>SQL Server Tools</li> <li>JSON Support in SQL Server</li> <li>Stretch Database</li> <li>Temporal Tables</li> <li>Columnstore Indexes</li> <li>SSIS Setup</li> <li>What Is New in SSIS 2016</li> <li>Key Components of a Modern ETL Solution</li> <li>Dealing with Data Quality</li> <li>Unleash the Power of SSIS Script Task and Component</li> <li>On-Premises and Azure Big Data Integration</li> <li>Extending SSIS Custom Tasks and Transformations</li> <li>Scale Out with SSIS 2017</li>
</ol>

Mastering SQL Server 2017

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