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SmartData Collective > Big Data > Data Mining > Mining for Gold in Your Data
Data Mining

Mining for Gold in Your Data

MindOverMachines
MindOverMachines
5 Min Read
Mining for Gold in Your Data
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Where to Dig and What to Look For

Infotech research giant Gartner defines data mining as the process of discovering meaningful correlations, patterns and trends by sifting through large amounts of data stored in repositories.

In short: “There’s gold in them hills!”

Where to Dig and What to Look For

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Infotech research giant Gartner defines data mining as the process of discovering meaningful correlations, patterns and trends by sifting through large amounts of data stored in repositories.

In short: “There’s gold in them hills!”

We are in the middle of a data gold rush these days, because processing and storage enable us to crunch gigabytes of data in minutes, and the cost of doing it all keeps coming down. Thankfully, this isn’t the Old West, and you shouldn’t come across anyone trying to stake the same data claim you’re after.

That’s because your data holds unique value for you.

When you mine data, you use your technical and intellectual skills to get insights out of information you already have. Start with information in whatever form you find it, use software to scrape it, reshape it, and spit out different variations, then take a step back to see how it gives you a new perspective on your business.

Where to Look

Check out the data you deal with every day. This can be found in every spoke of your operational wheel, including customer lists, financial transactions, and inventory tallies. Data leaves a footprint throughout the entirety of your supply chain—think about anything with a barcode—and in your history of interactions with customers.

Be creative—brainstorm different kinds of data, not just neat, easy-to-crunch numbers.

Remember to mine CRM platforms like SalesForce, and business networks like LinkedIn for more than just history or contact information. SalesForce data can be aggregated in multiple ways to simplify your business intelligence, such as identifying trends and providing marketing campaign results.  LinkedIn can tell you how many steps removed you are from your dream client, and each connection in common becomes a link in the chain that you can now count. This data helps you maximize your effort and get closer to the deal. 

What to Look For

You don’t always have to dig deep to find gold in your data. Sometimes it’s more like panning for gold in a stream.

Information flows through your organization all the time. What can you capture? Look for patterns and linkages that highlight big changes in the marketplace.

  • Correlations: When are buyers buying? One grocery chain moved beer closer to its diaper display after observing when dads shopped and what they bought.
  • Patterns: Does your user base look like it did a decade ago? Accounts receivable can show you which customers are ordering less and less from you—and which might be getting their goods elsewhere.
  • Trends: Which sales trends are temporary, and which are here to stay? If you’ve got years of data handy, you can step out of the moment and see long-term trends that lead to smart forecasting.

Without a doubt, spending time panning and digging for that gold in your data will help you find value. Data mining can also help you discover new competencies. If you pulled in public records info to give you the edge on which homes in a neighborhood might want your roofing services, you can bet basement water proofers will also be interested in that information!

As you add insights, you can turn data know-how into a service you can sell, in addition to an edge over your direct competitors.

Don’t forget that data mining is knowledge discovery; the real value comes with your perspective.

The next step to making data mining an advantage for your business is using the knowledge you’ve discovered to complement your strategic planning.

In the next edition of our Big Data series, we’ll take a look at how you can use data mining to make solid business decisions. 

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