The Forecast for Data Analytics in the Converged Cloud

Submitted by Morphlabs on May 02, 2012

Enterprises have been engaging in data analytics to mine for business intelligence (BI) for quite some time. Companies have long understood the value of extracting actionable information from their data sources for bottom line operational efficiency and top line revenue growth. While the Internet ignited an explosion of data, more recent innovations like social media, mobile devices and other real-time IP-instrumented machinery are causing this data growth to reach explosive proportions.

The recent Cloud Analytics Summit held at the Computer History Museum in Mountain View, CA showcased the high enthusiasm of both vendors and users for cloud based solutions to data analytics challenges. Companies are chomping at the bit for strategies to gain insights into consumer behavior, consumer sentiment and operational performance from the massive amounts of data they collect on an hourly basis.

The general reasons behind this enthusiasm are the same as those of others who are excited about the promise of the cloud. However the specific features that hit home among data analysts were scalable performance, elasticity, low entry points and convergence. Having the ability to spin up (and spin down) 100s or, in some cases 1000s, of virtual machines for a plethora of parallel data processing algorithms, in both the public and private clouds, is a game-changing tool for innovation. Companies can now ask new questions of their data in search of insights and market opportunities that will grow their business. They’re able to do so with less risk to time and valuable resources. In other words, they know with greater confidence, from a product and offering standpoint, “if they build it, they will come.” In addition, they can iterate through this “insight discovery, prediction and prescription process” more frequently and to their competitive advantage.

The marriage of data analytics and BI with cloud lowers the barriers for companies to find, create and capture newer, larger market as an early (or first) entrant. Some might call this the holy grail of doing business.

Our converged OpenStack-powered Dynamic Infrastructure Services mCloud solutions offer an ideal platform for data analytic workloads. It offers the key features aggressively desired by data analytics professionals: scalability, elasticity, high performance, low cost and converged infrastructure. You can read more about some of these specific business use cases here.



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