Microsoft busts 3 Big Data myths

By : |March 12, 2013 0

BANGALORE, INDIA: For some, big data looks scary. It reminds them of the additional expenses they have to incur in terms of infrastructure and specialised skillsets. Agreed, it will have its own set of challenges and the journey may not be as easy or as difficult as is being projected, however, it does bring along certain advantages. That is what Microsoft, which is positioning itself as a big data player, wants to convey as it takes down a few myths surrounding big data.

Myth No 1: It is too difficult for an organization’s IT stack to support big data from an infrastructure and scalability perspective

Eron Kelly, general manager, Microsoft SQL Server, writes, in a recent blog post, “Getting started with big data is less of a challenge than you might think and businesses can often take advantage of existing infrastructure and tooling investments to begin doing big data analytics now. Supporting big data from an infrastructure and scalability perspective is all about elastic scale and compute in the cloud at a reasonable price.

A recent study by ConStat (commissioned by Microsoft) found that nearly one-third (32 per cent) of 282 US businesses surveyed expect the amount of data they store to double in the next two to three years.

Myth 2: Employees with specialized experience are required to get the highest return from big data investments

“While it is true that the industry needs more data scientists, it is equally true that most organizations are equipped with the employees they need today to help them gather the valuable insights from their data that will better their business,” Kelly adds.

According to the Gartner’s Magic Quadrant for Business Intelligence and Analytics Platforms, the market for BI and analytics platforms will remain one of the fastest growing software markets.

“Although this is a mature market and has been a top CIO priority for years, there is still a lot of unmet demand. Every company has numerous subject areas – such as HR, marketing, social and so on – that have yet to even start with BI and analytics. Microsoft has long argued for the ‘democratization’ of BI, where individuals are empowered to do their own data analysis using familiar tools and without IT assistance,” he adds.

Myth 3: Big data is a challenge

Microsoft STB technical fellow Dave Campbell argues that it is more of an opportunity and says, in a blog post, “For all of us involved in big data, and me personally, it is an incredibly exciting time. The next 5-10 years are going to be breathtaking. I’m often asked, “Where is the ultimate value in big data and how do I tap into it?” There are two key measures in my mind: 1) time to insight, and, 2) return on accessible data. These measures are, in turn, enabled through a process I call information production.”

A recent Microsoft study revealed that 38 per cent of respondents’ current data stores contain unstructured data and 53 per cent rated increased amounts of unstructured data to analyze as extremely important. This trend is only increasing as businesses realize their unstructured data holds the key to new value not accessible in their existing structured data.

“Great information production tools allow you reduce the time to insight. They allow you to get from a hunch to validation very quickly. Valuable answers require logically joining different data sets – something every database person is familiar with. In traditional databases the ‘accessible’ data is constrained to data which is contained within the database. This data has been normalized, cleaned, and indexed so it can be used to efficiently answer a fixed set of questions over that data domain,” he adds.

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