I’ve been working recently with a small financial institution that has a significant need for analysis capabilities but does not have the budget for a lengthy project or expensive technology. The organization currently has a standalone marketing customer information file (MCIF) that provides precanned profitability and product ownership reports and a fairly robust householding engine. They also have call center reporting capabilities through a partial license for a popular business intelligence (BI) access tool that came with their newly installed customer relationship management (CRM) application. While these tools provide some analysis capabilities, both suffer from lack of integration (each presents a siloed view), both have little to no history and neither really fulfills the analysis needs.

While pondering the conundrum of large need/small budget, the client hopefully suggested, “How about a series of independent data marts that we could convert to a data warehouse later?” In this case, the organization really does understand the benefits of a data warehouse, so the question did not engender the panic that it might have if they were serious. Instead, it caused us to sit back and jointly work out a set of steps to enable them to construct a data warehouse in an environment with limited funding, limited resources and a shortened time to delivery. Here is what we came up with.

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