Big Data: Three Ways to Choose Meaningful Analytics

The NCAA tournament is going to start in a few weeks, and everyone is going to get their basketball winning prediction bracket ready.  Quicken Loans, insured by Warren Buffet, is offering $1 billion dollar prize for anyone picking a prefect bracket for the NCAA tournament.  While the odds for picking a prefect bracket are 1 to 9,223,372,036,854,775,808 according to the rules, it brings to mind that analytics of the teams or any company metric needs to be relevant to achieving the ultimate winning outcome.  The following focuses on three ways to choose meaningful big data analytics.

  1. Focus on the bottom line.  I have written several blogs on analytics – 5 Ways to get Analytics Started, 5 Success Factors, and 3 Criteria for Invaluable Analytics – that expose many analytics criteria, success factors, and other considerations when attempting to obtain meaningful information.  All of these are blogs have many great points, but unless your analytics effort is focused on the bottom line of your company, your analytics effort will be ignored.  A famous sport coaching quote says, “Winning isn’t everything; it is the only thing.” If you substitute the word “money” for “winning” in that sentence, your analytics will have the correct bottom line focus.

  2. Provide something significant within your analytics.  Customer segmentation analytics is being explored up to hundreds of different ways into fine micro-customer segments, but does your company really have the marketing budget or capability to address all these micro customer segments?  While micro customer segmentation is popular there are many industry data modeling techniques such as cluster analysis, association, product correlations, or life time value to name a few other analytical model types to analyze your business.  Analytics is a journey through the business and its data. Research your business data until your results show a significant company bottom line opportunity.  Significance is relative to the size of the company, but the significance of 1% or 2% can mean the difference of tens of millions of dollars to the bottom line. Those are the meaningful analytics your team needs to produce.

  3. Analytics should answer the tough questions management asks.  The analytics being discussed in the press these days is interesting because it focuses on easy analytic wins from new sources of operational, sensor, social, or mobile big data.  Having years of experience designing, building, and uncovering analytics through data warehouses and, more recently, big data systems I know it’s imperative to address management’s tough questions.  Just as I noted in the blogs mentioned earlier, as well the above two points, many existing reports that analyze different parts of the business exist already.  Your new big data system needs to do it all better.  Confirm existing reports, then provide the information faster or in real time, and provide better answers to the tough questions. Analytic systems that don’t provide the ability to enlighten and inform are just another reporting system, data warehouse, or money pit data silo.  Provide a design, data, and analytics that can provide real information, and management and users will continue to come back with more interesting questions.

These days analytics is driving new ideas in all types of ways at companies.  Big data provides a deeper and richer pool of information.  Follow these three ideas and your analytics will be successful and more meaningful within your enterprise.
Dave Beulke is a system strategist, application architect, and performance expert specializing in Big Data, data warehouses, and high performance internet business solutions. He is an IBM Gold Consultant, Information Champion, and President of DAMA-NCR, former President of International DB2 User Group, and frequent speaker at national and international conferences. His architectures, designs, and performance tuning techniques help organization better leverage their information assets, saving millions in processing costs.

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