Book Image

Introducing Microsoft SQL Server 2019

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

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)

Modern data warehouse patterns in Azure

In today's world, modern enterprises have recognized that all data represents hidden value waiting to be unlocked by their organization. Data exists in all shapes, sizes, and formats, and often the differentiating factor between the most efficient and successful companies and less successful companies is how well those companies use data to drive intelligent decisions. More companies are recognizing that data and intelligence have little value if we can't properly manage it.

Today organizations need to be able to ingest large volumes of data into big data stores from a variety of data sources. Once in big data stores, Hadoop, Spark, and machine learning pipelines prepare and train the data. Once the data is ready for complex analysis, the data is loaded into the data warehouse to be accessed by business intelligence tools, such as Power BI or Excel. Azure provides the framework and ecosystem for designing and building cutting-edge...