With all the excitement about the possibilities of big data, and the great advances we've seen in storage and processing technologies, it's easy to forget an important fact: Data ages. What starts out timely and relevant can, over time, become irrelevant and downright misleading. And there's no simple way of telling which data is aging gracefully and which is causing problems.
Data management must not be just about setting up great systems and processes. Nor is it just about encouraging and modeling best practice across the organization, so that the business gets the best possible value from its data. It's also about maintaining the data asset – ensuring the data you hold really is an asset to the business.
Jeff Kalter, writing in the context of marketing data, recommends paying attention to data profiling and cleansing. I wonder if these vital housekeeping jobs are prioritized in our organizations today. There's some incentive for frontline sales and marketing folks to do these jobs, since they don't want to be wasting time and money communicating with people who are no longer in the frame. However, every data management team should have guidelines and a schedule for profiling and cleansing.
Kalter's third recommendation goes beyond data management. He talks about gathering intelligence. I guess this fits with assessing the business context to ensure that relevant data is being collected. At the strategic or corporate level, I'd suggest that your industry data standards body delivers this service. By maintaining, extending, and updating standards in line with business evolution – as understood and guided by industry participants – data standards encapsulate and embody the changing business context of your vital data. Marketing Executives
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