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Introducing Microsoft SQL Server 2019

You're reading from   Introducing Microsoft SQL Server 2019 Reliability, scalability, and security both on premises and in the cloud

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781838826215
Length 488 pages
Edition 1st Edition
Languages
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Authors (8):
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Allan Hirt Allan Hirt
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Allan Hirt
Dustin Ryan Dustin Ryan
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Dustin Ryan
Mitchell Pearson Mitchell Pearson
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Mitchell Pearson
Kellyn Gorman Kellyn Gorman
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Kellyn Gorman
Dave Noderer Dave Noderer
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Dave Noderer
Buck Woody Buck Woody
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Buck Woody
Arun Sirpal Arun Sirpal
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Arun Sirpal
James Rowland-Jones James Rowland-Jones
Author Profile Icon James Rowland-Jones
James Rowland-Jones
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Toc

Table of Contents (15) Chapters Close

Preface 1. Optimizing for performance, scalability and real‑time insights 2. Enterprise Security FREE CHAPTER 3. High Availability and Disaster Recovery 4. Hybrid Features – SQL Server and Microsoft Azure 5. SQL Server 2019 on Linux 6. SQL Server 2019 in Containers and Kubernetes 7. Data Virtualization 8. Machine Learning Services Extensibility Framework 9. SQL Server 2019 Big Data Clusters 10. Enhancing the Developer Experience 11. Data Warehousing 12. Analysis Services 13. Power BI Report Server 14. Modernization to the Azure Cloud

Data virtualization use cases

In this section, you will review three specific scenarios where a modern enterprise data hub implemented using data virtualization technology adds significant value to your solution.

Data virtualization and hybrid transactional analytical processing

One approach that has gained popularity in recent times is operational analytics, also known as hybrid transactional analytical processing (HTAP). With this approach, you blend the operational workload and the analytical workload into a single system for that dataset. This has the advantage of consolidation and can limit data duplication. It also addresses data quality issues at the source, which leads to a reduction in the data management burden. However, there is a notable downside. Most enterprises have multiple-source systems, which would result in multiple HTAP systems. This introduces the challenge to users of querying across all their analytical data.

Enter your modern enterprise data hub....

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