A popular question that IT executives around the globe are asking is, “What are your plans to deal with Big Data?”
The Internet is all abuzz with people trying to figure out how to manage Big Data problems, but I want to expand that conversation to include Little Data. First, a quick definition of Little Data: the unique data about the customer, the vendor, the location, the interaction, etc.; Big Data is all of the information in the enterprise about everything. To say it a different way, Big Data needs context (or Little Data) in order to be useful.
When Big Meets Little
Let’s use an insurance example that is relevant to almost everyone. Through Big Data analysis using Spotfire and actuarial expertise, insurance analysts can create models that effectively identify risks based on age, gender, medical history, habits, body measurements, and more. However, these models are worthless until they are combined with the Little Data (context) of your personal characteristics. It is only when the Big Data is combined with Little Data that it allows the insurance company to correctly understand risk and create a competitive, but profitable price.
Bigger is Not Always Better
The business magazines, analysts’ reports, and business blogs are filled with advice on applying Big Data tools to create value from your historical Big Data archives. Many of them skip the most important aspect of applying the context through Little Data. You need to quickly gather, analyze, and apply your real-time interactions that are stored in your ERP, CRM, HR, and eCommerce systems. This information should then be combined into an encyclopedia of information housed in a Master Data Management system for common access to all systems.
When your data strategy includes both Big Data and Little Data, you have the knowledge gained from years of experience used in context with the immediate situation. This is what gives your organization the two-second advantage in business.