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SmartData Collective > Big Data > Data Mining > Take a Little Bite Out of Big Data
Big DataData ManagementData Mining

Take a Little Bite Out of Big Data

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Take a Little Bite Out of Big Data
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Easing Fears About Big Data Hype

So, everyone’s talking about Big Data. (And I mean everyone.) People want it, need it, think they need it, aren’t sure if they need it and, in some cases, already have it and aren’t sure what to do with it. Let’s break down Big Data and gain a little more perspective around the business of problem solving.

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  • Easing Fears About Big Data Hype
  • Easing Fears About Big Data Hype

Easing Fears About Big Data Hype

So, everyone’s talking about Big Data. (And I mean everyone.) People want it, need it, think they need it, aren’t sure if they need it and, in some cases, already have it and aren’t sure what to do with it. Let’s break down Big Data and gain a little more perspective around the business of problem solving.

The problem you think you have: We have so much data and we’re losing money every day by not acting on that, while our competitors have surely figured out how to leverage their data using Big Data solutions.

The solution you think you need: Our IT department should start analyzing and reporting on Big Data.

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The problem you really have: You don’t know how to start looking at your data differently. Your IT department can tell you which data are available but not always which data are valuable. In other cases, you may know which data are valuable, but are not doing enough to capture them today.

The solution you really need: A “now data” solution instead of a “Big Data” solution. The fact is, most businesses do not have the IT resources required to implement a true Big Data solution. While there is high interest in capturing and using data, most companies are still stuck with legacy tools, disconnected solutions and no connection between operational plans and business reality.

Now Data Instead of Big Data

Find out what value you can get out of your systems and processes – right now – with the highest value proposition, in the shortest amount of time (30 days), and at the lowest cost.

Be agile like a startup and go for the quick hit. It’s like a jump-start: one to two days to implement, and 30 days to see results. Then lay the foundation for the immediate future. You might even “duct tape” the implementation of the quick hit—that’s all right! The low cost and low risk make it okay. And the “big” ROI?  You’ve gained new insights into your data that can now be used to start building your longer-term Big Data solution. It’s a win-win.

Check out these real-world examples of companies that took a little bite out of Big Data for even bigger results:

  • National Registered Agents, Inc. (NRAI) – Used existing databases to rank prospects by size and clustered them by geography, so their sales team could focus its efforts on the best targets. Read more >
  • The Association of Manufacturing Technology (AMT) – Converted a labor-intensive data capture process into a more time/cost efficient process that provided faster and more timely access to the data they were already collecting. Read more >

Planning for the ultimate Big Data solution can prove costly. Often, reports that are thought to be valuable (and thought to be automated) are done by hand behind the scenes and are extremely expensive. There are data solutions, whose foundations are in place right now that can be leveraged, improved and better implemented almost immediately. Don’t necessarily look for the largest value item, but instead look for the solution that provides the largest value for the lowest cost to develop and maintain. Then use that value created to offset the cost of (or to invest in) a bigger Big Data effort.

Remember, it’s not the technology you need to focus on first…it’s the business problem you’re trying to solve. Let that conversation drive your technology conversation—and your “small-medium-large” data technology solution.

The new shiny object (aka Big Data) does not invalidate all that has come before it. Look at what you have and really find out if you’re making the most of your data—no matter how much or how little you have.

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