Big Data: 3 Keys for Effective Big Data Success

Companies are more stressed and looking for every advantage or differentiator to gain the competitive advantage.  Working with Big Data is in IT fashion as a way to gain new insights from customers, suppliers and partners for delivering the best products, customer service and profits.  Executing these Big Data initiatives is always an interesting opportunity as most C-Level executives depend on their IT leadership to architect and deliver golden insights for bottom line improvements.

The following are three keys to building an effective Big Data project that delivers business results.

  1. Look at your business Big Data issues first.  As David Brooks highlights in his article “What Data Can’t Do,” there are many things that data can’t do.  As he says, and I paraphrase, “just because the haystack gets bigger doesn’t mean that the needle we are looking for is going to be easier to find.”  Corporations need to frame their Big Data issues properly.  Your Big Data initiatives need to discover or use new attributes or new ideas that can affect real tactics and business improvements.  Looking at the business with a bigger sample data set doesn’t make you smarter, but asking new or better business questions of the Big Data will get actionable business improvement answers.  
  2. Acquire and use Big Data that makes a difference.  With these Big Data initiatives there is an opportunity to get a large and wide range of internal and external data from all types of operational, social, media and sensor data.  When choosing your Big Data input sets make sure to get the right sources of data.  Having the right data sources, types and context for your Big Data input will give your analysis the richness, variety and value you need from its attributes.  
  3. Analyze attributes that confirm and optimize your product or services scenarios.  While analyzing the attributes of your Big Data, the sample size can become overwhelming and can lead to many ideas and conclusions that may or may not be correct.  Develop Big Data analysis or business formulas that test proven known scenarios within your business and then extend your analysis to expand your business knowledge.  This provides confirmation of existing business practices and helps everyone understand the Big Data content, how it’s processing addresses the business issues and insures that the analysis is valid.  The properties of the Big Data attribute analysis should lead your business to tangible actionable items such as better marketing plans, better product margins, better customer responsiveness or just plain more unit sales.  

Make sure the business issues are discussed within the correct Big Data context, attributes are used and advanced analytics are properly formulated to address the issues are the keys to finding the needle of insight for your Big Data success.

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Have you made your plans for IDUG in Orlando this year?  Also the make sure to register early and get the IDUG early bird discount. Sign up today!

I look forward to speaking at the IDUG DB2 Tech Conference 2013 North America conference.  The conference will be held in Orlando, Florida on April 29-2, 20132.  Get more information at www.idug.org.

I will be speaking at the conference presenting Session F07 – “Data Warehouse Designs for Big Data Performance” on Wed, May 01, 2013 (02:15 PM – 03:15 PM) in Bonaire 5 & 6.

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Dave Beulke is an internationally recognized DB2 consultant, DB2 trainer and education instructor.  Dave helps his clients improve their strategic direction, dramatically improve DB2 performance and reduce their CPU demand saving millions in their systems, databases and application areas within their mainframe, UNIX and Windows environments.

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