3. Rent to own
If you had the right question but didn’t find the answer on the first round of analysis, now it is time to bring in the big data magic.
Before you fill out the CapEx request for hardware, software and implementation costs, think “Cloud”.
Services like Amazon’s EC2 enable you to create your own analytic sandboxes, and you pay on a usage basis. You can fire up an environment to do some initial testing and turn it off when you’re done, paying just for the time you used.
When your initial experiment is a success, you can scale that environment up to handle the full Big Data load. And, when the project is completed, you just turn it off. Capex becomes OpEx, total cost for your project goes way down and you can use a fail-fast model to test many possibilities before funding an initiative through to completion.
Even if you need help, it is still unlikely to be time to employ a data scientist. Because you defined your question well and have done the initial analysis, you’ll know enough to engage a targeted consultant. Not a big data generalist, but someone who has experience with the specific types of problems you are trying to solve.
Options abound from big consulting shops to a graduate or doctoral student whose thesis is in your area of interest. Engage them on the specific problem and move from there.
Business is increasingly becoming a data-driven game. Even marketing departments are increasingly run by data-driven behavioural economist types rather than the creative copywriters of a decade ago.
This shift isn’t about any given technology. It is really about a mind-set. Focus on problems that matter, define measurable methods for understanding and managing those problems and use analytics (big or small) to create value by solving those problems.
Charles Caldwell is the director of solutions engineering and principal solutions architect for Logi Analytics.
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