My colleagues and I were recently presented with an interesting challenge while building out a business intelligence solution for a mid-size client. The client wanted to archive, for potential future use, a large amount of data over and above the current reporting requirements. Unfortunately, the client’s proprietary database system was primarily designed for data analysis, not storage, and could not be leveraged as a solution. To identify a solution, our collaboration focused on evaluating options made possible through significant changes in the data analytics field. As we discussed the new technologies and methodologies, I found myself drawing parallels to how Apple Macintosh, in 1984, brought computing power from the mainframe to the masses.