Increase Your Analytics Intelligence with Microsoft SQL Server*

Rapidly growing volumes of data (IDC predicts a ten-fold global increase by 2025 to 163 zettabytes1) are just one of the challenges facing today’s business and IT leaders. This growth is paralleled by an increase in complexity as the types and formats of data available also multiply. However, advanced analytics capabilities like machine learning and artificial intelligence (AI) can help organizations take control of this data deluge and turn it into insight.

This, in turn, is driving the emergence of disruptive business models that are setting new standards and creating new competitive benchmarks. All this change is happening at an accelerated—and accelerating—pace, which is having a significant impact on the business landscape and the average lifespan of a company. For example, in 1964, the average tenure of a company listed on the S&P 500 index was 33 years, but, by 2027, this is expected to shrink to just 12 years2.

Those able to beat this average and stick around for the long term will be those that take advantage of advanced analytics capabilities to keep up with the real-time pace of business.

Microsoft SQL Server*: An Analytics-Ready Database

For many organizations, a core part of their strategy to achieve this data-driven vision is having a strong operational database management system in place. One of the most common choices for this is Microsoft SQL Server*. These solutions are designed to help improve the performance and availability of mission-critical analytics applications, by offering in-memory online transaction processing (OLTP) and real-time operational analytics, combined with advanced compression, flexibility, and availability benefits.

With its in-database advanced analytics capabilities, Microsoft SQL Server enables businesses to conduct real-time operational analytics or predictive analytics with operational data without compromising performance. This is, in part, made possible by taking advantage of in-memory technology that delivers superfast reads and writes.

Microsoft SQL Server Machine Learning Services* now provide comprehensive support for building and deploying machine learning solutions in either R* or Python*, two of the most popular languages with data scientists that are built right into Microsoft SQL Server. This means there’s no need to move the data out of the database to do modeling. R and Python code can now use the multi-threading and massively parallel processing inherent to Microsoft SQL Server.

Intel® Select Solutions: The Power Behind the Scenes

Unfortunately, many organizations using Microsoft SQL Server today are unable to take full advantage of these advanced analytics capabilities, as the infrastructures on which they run the solution are aging, and thus not delivering the required performance.

As the needs of the business and its applications become greater and more complex, and online security threats continue to emerge, it’s essential to ensure IT platforms are up to the challenge. This is why Intel has worked closely with Microsoft to develop two verified hardware and software stacks that are optimized for specific software workloads across compute, storage, and network:

Intel® Select Solutions for Microsoft SQL Server Business Operations

Powered by the latest generation Intel® Xeon® Scalable processors, these reference designs deliver a verified hardware and software stack designed to ensure that the platform running the Microsoft SQL Server environment and applications delivers excellent performance.

Two configurations (Base and Plus) have been optimized for OLTP workloads, simulating a medium to large wholesale supplier with multiple warehouses and a large number of transactions.

Intel® Select Solutions for Microsoft SQL Server Enterprise Data Warehouse* (EDW)

Also powered by Intel® Xeon® Scalable processors, these reference designs offer outstanding performance for data warehouse solutions. They are designed to provide a fast track to taking advantage of big data —both structured and unstructured—massive data volumes, and rapid data analysis.

The Base and Plus configurations help ensure a right-size data warehouse solution across different environments in order to support the needs of a wide range of business types and sizes. The Base configuration is designed to accommodate mainstream businesses’ data warehouse needs, whereas the Plus configuration is designed for larger data sets. Both configurations are tuned for excellent performance in latency-sensitive data warehouse environments.

Each solution stack also includes Trusted Platform Module 2.0, Intel® Hyper-Threading Technology, Intel® Turbo Boost Technology, and Intel® Speed Shift Technology. Learn more about the solution configurations in these solution briefs:

Or discover how advanced analytics can help transform your business, visit www.intel.com/analytics.


1. Data Age 2025: The Evolution of Data to Life-Critical, IDC, 2015. https://www.seagate.com/files/www-content/our-story/trends/files/Seagate-WP-DataAge2025-March-2017.pdf

2. 2018 Corporate Longevity Forecast: Creative Destruction is Accelerating, Innosight, 2018. https://www.innosight.com/insight/creative-destruction/

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About Ken LeTourneau

Ken LeTourneau has been with Intel for 20 years and is a Solutions Architect focused on Big Data and Artificial Intelligence. He works with leading software vendors on architectures and capabilities for Big Data solutions with a focus on analytics. He provides a unique perspective to leading IT decision makers on why AI is important for 21st century organizations, advising them on architectural best practices for deploying and optimizing their infrastructure to meet their needs. Previously, Ken served as an Engineering Manager and Build Tools Engineer in Intel's Graphics Software Development and Validation group. He got his start as an Application Developer and Application Support Specialist in Intel's Information Technology group.