Zooming in on Big Data

“Big Data” has completely changed the landscape of doing business. It’s really a story of a few leaders adopting data as a tool and the industry falling into line thereafter.  Google, eBay and LinkedIn were some of the first to orient their organizational strategy around driving business intelligence through increased data Big Data - Dynamic Questquantity, quality and variety.  This drove higher demand for data across industries as these three began to influence other industry players and business models based on their success with using data as a lynch-pin to strategic growth.  And as you might guess, the more prevalent the emphasis on data became in the war rooms across the globe, the more suppliers across the service chain began providing data accessibility to the marketplace.  Data has now become widely available and in more wide-ranging formats, types and contexts; and data as a key component to strategy has moved from “nice-to-have” to “can’t-do-without.” In fact, the term “Big Data” is a reference to the variety and availability of data as a single large information source.  In addition, “Big Data” infers analysis. When given a tool like quality data in relevant quantities and variety, it is assumed that the data is useful only when pooled together and analyzed to guide decision-making and strategy development.

Big Data Done Right

When done correctly and with proper analysis on good data, insights are the result which inform decisions and strategy.  This cycles into a consistent flow of data and business intelligence leading organizational decision-making, and company success and growth naturally follow.

Here are some of the top benefits we hear from our clients when we deliver data analytics solutions for them using Big Data.

  • Real-Time Monitoring and Timely Insights – Analysis on Big Data provides deeper understanding and insights, such as prevailing cause-and-effect relationships – and the analysis leverages large amounts of data across a wide-variety of sources (e.g., internal databases, third party databases, the internet, social media platforms, and tons of others).  But one of the greatest benefits we hear from our clients is the timeliness of Big Data.  Because Big Data has virtually unlimited availability, our clients have found enormous value when data analytics solutions are engineered to use its near-constant data flow. When constructed that way, the data analytics, reporting or BI solution stops being a lagging indicator of historical performance and starts acting as a source of actionable insights to guide decisions and strategy as they arise.
  • More Reliable Forecasting – Analytics solutions created against the volumes of information that naturally are associated with Big Data often reveals patterns that guide future goal setting and estimates. These patterns make it easy to forecast future events and shift estimates and forecasts when anomalies in the observed patterns arise.
  • Better Decision Making – The benefit to Big Data is not only the readily available flow of data, but also the sheer volume of data. So many strategic decisions are based on averages, (e.g. the average sales per quarter, the average close rate, etc.). Here’s a quick stats question for you: what happens to the standard error of a mean when the “n” goes up? You guessed it. The error goes down.  That means those averages you base decisions on and track performance around begin to have less variability and, simply put – your average becomes a more reliable indicator and input when it comes from a big data set.  As the name indicates, big data is, well, BIG.
  • Risk Mitigation – What happens if you increase your efficacy in estimating, decision-making, forecasting, strategy development, and plan execution?  Your overall strategic risk decreases.  This means that as you improve your ability to get meaningful, decision-driving insights from Big Data, you reduce the risk and likelihood of unplanned and unforeseen mistakes that result from poor input, insights, and strategy.

The Key Three V’s of Big Data

There are a handful of criteria that define whether your analytics are based on Big Data or not. We like to call these the “Key Three V’s of Big Data.”

  1. Volume – The more information there is to process, the more reliable the statistical insights, the lower the standard error and variability, and the higher confidence you can have in the intelligence you derive from the data.  For example, Facebook is often a good target for data gathering around sales target demographics and behaviors because around 500 terabytes of data is generated by Facebook users every 24 hours. Big Data volumes can often be so large that they are beyond the capabilities of traditional data processing tools and require custom development of analytics solutions to get to the valuable insights held within the data.  Too much information is a good problem to have, and is a defining criteria for your data to be called “Big Data.”
  2. Velocity – The higher the frequency of data capture, the better. Behavior patterns shift and insights on causal relationships are most actionable when there’s still something to take action against. If the campaign or initiative is complete and your analysis gives you the ancient history alone, there may be adjustments you can make in the future, but there will be little you can act on to change the outcome of the now completed strategy. In order to be agile and shift direction and execution based on data-based insights, the data has to be readily available and quickly refreshed to ensure action is based on what is current.
  3. Variety – Big Data is not composed of a single source.  By definition, the data is varied, most often from a number of different data sources so that the multi-variate relationships and data influencers paint a more holistic picture of the key data-based measurables and avoid blind-spots in the analysis.

Ready to start putting together your Big Data strategy?

If you are interested in devising a Big Data strategy that fits your business, we’d love to help. We have a team of seasoned data engineers, analytics experts, and IT professionals that are ready to help you come up with the right Big Data solution for your organization.  Click the button below and we’ll help answer any questions you might have and put you on the right path toward making use of Big Data.

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