The original purpose of a data silo was to keep secrets. People have been keeping secrets for a long, long time. Prior to the written word, keeping a secret meant not sharing specific information with anyone else, verbally. And then came the written word. Secrets could be shared accidentally, or even stolen. Life became more complicated, but in some ways, more efficient. Then came mathematics, eventually followed by the computer, which stored information in the form of data. Computers also store secrets and some of those end up in data silos, whether purposefully or just from years of doing business in the same way.
A data silo is ostensibly meant to keep private information from the eyes of those who do not need to know. Unfortunately, information that is needed by others may also stored in the data silo. In the worst-case scenario, a silo becomes a dumping ground for data that “might be” useful sometime in the future, and then sits there, never used.
Data silos often contain “incompatible data” that is believed important enough for translation at later a time. For many organizations, a significant amount of data was stored for later translation. The inappropriate, and all too human, tendency to “stash” potentially valuable information in a convenient and “safe” place (such as a data silo) has created a significant problem for Big Data Analysts.