I saw this quote recently and think it’s dead on: “‘Big data’ is what happens when the cost of storing information gets less than the cost of throwing it away.” – George Dyson at Long Now

This is SO true. Far too many of my clients are hoarding data, not because they are hoarders, but because it is so much easier and cheaper to keep data than to purge it.

This creates a challenge when it comes to analyzing data. My clients have a sense of “information overload” and are generally timid about analyzing data, because there is so much of it.

But part of analyzing data is identifying the data that is NOT useful for analysis. Others will disagree, but among my rules of thumb are that sales data over three years old is relatively useless, as is other engagement data (e.g., committee service, awards) over three years old. Sure, an argument can be made for exceptions, but speaking generally, data this old tends to have diminishing returns.

So if you’re having trouble deciding which data to analyze, start by eliminating the data you don’t need to analyze. That may make the challenge much simpler to attack.