BUSINESS INSIGHTS

Aug 30, 2013

Is SQL Server Analytics Platform System a Game Changer?

Posted by Anthony Mattas

by Anthony Mattas and Rob Kerr

A recent MIT Sloan Review Article reported that “Modern enterprises are awash with data, and in most organizations the volume of data is expanding by 35%-50% every year”. To keep up with rapid data growth, CIOs need to plan for more scalable platforms to power their data warehouse and analytics platforms. Microsoft SQL Server Parallel Data Warehouse 2012 (PDW) helps organizations cost-effectively scale their analytical capabilities as never before.

The second generation of PDW, released in 2013, evolves the platform in ways that embrace the future demands of data warehousing. PDW delivers an appliance well suited to deliver a Modern Data Platform capable of analyzing any type (structured or unstructured) and of any size.

While PDW provides many innovations and improvements, four stand out as strategic game changes CIOs should consider when evaluating data warehouse and analytics strategies.

PolybaseHadoop Elephant

Unstructured and high volume data are the two fastest
growing types of enterprise data. Social media, customer feedback, and sensor data often require a non-traditional approach to analysis. New distributed processing technologies, like Apache Hadoop, have become the go-to technologies to address these new challenges. But implementing emerging technologies with traditional data warehouse and business intelligence platforms pose new 
challenges.

Microsoft recognized the need for enterprises to manage risk when integrating Big Data technologies like Hadoop with existing Enterprise Data Warehouse (EDW) and business intelligence platforms to enable users to fully understand their business.

Polybase is a new, ground breaking technology which allows EDW users to leverage PDW and Hadoop from a single query interface.

This integration allows organizations to merge large volumes of non-relational data stored within Hadoop with their traditional enterprise data. Customers can continue to use their existing analytics tool set to analyze their organization’s “big data”.

xVelocity Columnstore Indexes

xVelocity is an in-memory technology originally introduced with PowerPivot in 2010. The core technology provides an in-memory columnar storage engine designed for analytics. Storing data in a xVelocity provides extremely high compression ratios and enables in-memory query processing. The combination yields query performance orders of magnitude faster than conventional database engines.

In PDW 2012, Microsoft has further enhanced the xVelocity engine to support updatable column store tables, making it possible to use xVelocity as the native storage engine for EDW data. Combining xVelocity and PDW V2 combines fast, in-memory technology on top of a massively parallel processing (MPP) architecture.

Workload Management

ImagineGears yourself as the CEO of a large enterprise on the last day of your fiscal year itching to keep a pulse on your organizations sales results, only to be blocked by a routine maintenance process consuming a large amount of appliance resources.

With PDW 2012 workload management, database administrators
have the ability to divide the appliance workload into four resource classes: default (small), medium, large, and extra-large. The appliance allocates resources across the four different resource classes. By managing resource class assignment, DBAs have enhanced control over workload prioritization and resource allocation they need.

Cost Efficient Architecture

Hundred Dollar BillsA key reason to consider appliance architectures is to achieve
the lowest TCO for a high performance tier 1 platform. Cost reductions were achieved by eliminating expensive hardware SAN, instead employing new Windows
2012 Storage Spaces
features in conjunction with hardware virtualization to achieve superior performance and availability with dramatically lower appliance costs.

With the new storage design, PDW uses a single Hyper-V cluster across the entire appliance and Infiniband interconnects. This design provides seamless failover within the appliance for both node and disk failures.

Additionally, the new hardware architecture provides significant performance improvements, a 10 fold increase in storage, and almost a 50% lower cost per terabyte compared with competitor offerings.

Summary

It's long been known that the effective use of information can directly contribute to the competitiveness and effectiveness of most organizations. Yet only recently has it become cost-effective for organizations of all sizes to acquire technologies capable of analyzing large volumes of detailed information.

By combining both MPP EDW capabilities and unstructured analytical capabilities in a single, easy-to-manage appliance, SQL Server Parallel Data Warehouse (PDW) well positioned to help organizations use information to enhance their competitive position.

Want to learn more about using Parallel Data Warehouse, Apache Hadoop and advanced analytics in your organization?  Contact BlueGranite to find out how we can help your organization use information as a strategic asset.

 

 

 

 

 

 

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Anthony Mattas

About The Author

Anthony Mattas

Anthony is a former business intelligence consultant with BlueGranite, dedicated to delivering cost effective solutions that empower the business to make strategic decisions. Anthony is currently a solutions architect with Microsoft in the Heartland District.