Finding Big Value in Big Data

big-dataIn the past year or so, Big Data quickly has evolved from what some characterized as just another popular catchphrase into an established new era. But hype doesn’t automatically transform a buzzword into a best business practice. A number of factors, such as measurable results, continued focus and sustainability, dictate whether a concept is much more than just a fad. The essential question is this: does big data actually solve real-world business problems? The short answer is: absolutely  – but more time is required to see full adoption across a broad spectrum of industries.

Big Data Means Big Business

According to industry analysts, structured and unstructured data collected by enterprises continue to grow at exponential rates. Volume and Velocity, two of the 3 V’s of big data understood by the business world as the “Big Data Problem” – are becoming less of a concern than the Variety of data. Increasing power in processing hardware and data storage are generally able to match the growth in volume and velocity, but variety remains more of an enigma.

Enterprises typically divide up data assets in separate and distinct silos – finance, sales, marketing, operations, and supply chain management. Due to the variability of data across silos, analytics can’t cross these data bridges in order to gain an accurate, enterprise-wide view of revenue and costs. In fact, many business and IT managers accept the lack of analytical collaboration as a given, an inevitable limitation. As a result, as data content continues to grow, corporate “knowns” are increasingly outpaced by “unknowns.” Precision within individual silos is clear, but this view does little to inform effective strategic direction for the enterprise as a whole.

There is a better way to tackle this challenge in variety by seizing the opportunity presented by big data.

An Enterprise View

Historically data silos have individually managed data content that is relevant to the needs of the sponsoring corporate unit: department, product group, subsidiary, geographical region, etc. This has resulted in enterprise-related data being dislocated into disconnected segments across the silos. An important big data challenge requires aggregating the data across these silos for an overarching view of the organization. The purpose of the aggregation is to reveal the correlations across the business units for strategic insight. This big data challenge requires solutions that can harness the intelligence from the data and deliver actionable intelligence to the business user. Traditional data warehouse and BI tools aren’t designed to analyze, identify and surface critical data relationships and correlations. As a result of this limitation, critical insights, perspectives and market opportunities remain hidden from view because business users don’t know what they don’t know.

These critical connections and correlations are vital to managing big data and allowing enterprises to see a more comprehensive image of their products based on actual customer-buying patterns. Used in this manner, big data reveal valuable information quickly, accurately and allow for rapid, more relevant decision-making.

Freeing up the data to reveal associations and correlations through big data analytics solutions will paint a bigger picture – one that can better streamline sales by shedding light on what customers are buying, in addition to where, when and how. Previously, companies would pile their quasi-structured data into spreadsheets, requiring teams of data analysts to interpret and derive meaning. This is not a scalable solution and often misses the obvious target. Big data demands applications that can interpret and deliver immediate results to business users.

An Important Point in Time

We’re presently at the stage of the big data era in computing where an increasing number of enterprises are working to adopt the methodologies described above. It may take several more years before we see a big data ecosystem evolve to the point where localized data silos become global in perspective, but the road toward this goal is well-traveled right now, and there’s much more Big Value in store.

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