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  • Book Overview & Buying Introducing Microsoft SQL Server 2019
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Introducing Microsoft SQL Server 2019

Introducing Microsoft SQL Server 2019

By : Kellyn Gorman , Allan Hirt , Dave Noderer , Mitchell Pearson, James Rowland-Jones , Dustin Ryan , Arun Sirpal , Buck Woody
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Introducing Microsoft SQL Server 2019

Introducing Microsoft SQL Server 2019

By: Kellyn Gorman , Allan Hirt , Dave Noderer , Mitchell Pearson, James Rowland-Jones , Dustin Ryan , Arun Sirpal , Buck Woody

Overview of this book

Microsoft SQL Server comes equipped with industry-leading features and the best online transaction processing capabilities. If you are looking to work with data processing and management, getting up to speed with Microsoft Server 2019 is key. Introducing SQL Server 2019 takes you through the latest features in SQL Server 2019 and their importance. You will learn to unlock faster querying speeds and understand how to leverage the new and improved security features to build robust data management solutions. Further chapters will assist you with integrating, managing, and analyzing all data, including relational, NoSQL, and unstructured big data using SQL Server 2019. Dedicated sections in the book will also demonstrate how you can use SQL Server 2019 to leverage data processing platforms, such as Apache Hadoop and Spark, and containerization technologies like Docker and Kubernetes to control your data and efficiently monitor it. By the end of this book, you'll be well versed with all the features of Microsoft SQL Server 2019 and understand how to use them confidently to build robust data management solutions.
Table of Contents (15 chapters)
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Big data overview

The first magnetic storage devices were, large, bulky, and expensive, and required massive amounts of power and cooling. They also failed quite often. But, as time has progressed, the sizes of computing components – especially storage – have shrunk, and costs have decreased. However, the capabilities, reliability, and power of those components have increased. This allows us to store much more data, and since we've had those technologies longer, we've been able to store more data over time.

And what can we do with it all — why keep it? Given a system that processes and delivers the data quickly enough, there are actually quite a few examples of specific use cases for large sets of data. The most basic use of big data is to simply query it, using standard T-SQL or Multidimensional Expressions (MDX).

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