Big Data: Three More Ways to Choose Meaningful Analytics

Last week I talked about ways to choose meaningful analytics. Here are three more ways to make the analytics even better for your big data project.

  1. Focus the analytics only on a specific business aspect.  Last week I stressed analytical focus on the money aspects.  This week we need to take that focus one step further to focus our analytical efforts on a particular business aspect.  For example, analytics are being done for all type of situations customer, products, location sensors etc….  To start, focus on only one of those aspects and make it better.  Keep it simple, keep it to a single aspect, and make sure to be successful with that single aspect, and only then incorporate more aspects or other factors.  Start by focusing on getting more customers or promoting a product, or developing location optimization, focus the project success on one aspect for the concentration of everyone on the team.

  2. Leverage success into more analytics success.  By concentrating on success of the single or first business aspect the entire management, project team, and business users realize the components, data quality issues, cleansing processes, and result verification procedures necessary for a successful big data project.  Infrastructure components, computing capacity and software are verified for delivering impactful analytics for the bottom line.  Now, leverage all that business process knowledge to another aspect of the business.  Apply all the same rigor and replicate your success for another company division or another business dimension.  If the first analytics project was customer related, now do something to analyze your businesses products’ aspects.  Keep the analytics focused to this new area and use every previous success component to start leveraging and refining your analytic procedures into another success.

  3. Leverage your analytics into more business segments.  Use these core focused analytics to expand into more derivatives to detail more aspects of the business into more finely grained analytics.  Once the bigger themes of the customer, product, location, or sensor data are realized, drive more finely grained analytics to slice the business process pie into finer slices.  Using this type of finer grain analytics, the business and the analytics team can observe when the business analytics concepts begin to change or break down.  Understanding when a business concept breaks down is as important, sometimes more important, than discovering the bigger trend.  Use your analytics not only to prove a concept, but also set the analytics process guidelines to tell when the trend or concept breaks down through more segments or stretching the analytical concept.

These days big data business analytics is the new frontier of business innovation, making your data work harder through closer inspection and evaluation.  Use these three ideas to choose meaningful analytics and drive them through iterative business success procedures to realize new and richer understanding of your business.


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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