Cleanup in Aisle One
Clean data is vitally important. But the sad thing is that the definition of ‘clean’ is arbitrary. In absolute terms it means that all elements of a data set are accurate, but in very circumstances is that even possible. Data has a freshness date, but older data is not removed. It may be archived or even updated, but more often than not it is just left to rot. Rotten data doesn’t turn into compost that can be used to nourish new data. While everyone talks about clean data, it is almost a mythical creature.