Credit unions can benefit greatly from collecting and storing information to leverage Big Data. The cost of building a data warehouse can be steep, though. If you’re considering building a data warehouse for your credit union, it’s important to know what you’re getting yourself into.
The benefits of building a data warehouse speak for themselves in the financial world. Getting into the data analytics game isn’t cheap, however. It’s not as simple as just buying a data warehouse and watching a video tutorial; no, getting started requires a large initial investment as well as ongoing support and upkeep costs.
Here are a couple of the common issues associated with building a data warehouse for the credit union industry.
Initial Investment Costs
There are two major expense considerations for any enterprising credit union looking to construct its own data warehouse. The most pressing of the two is the financial cost, and the second is the time invested. Because we’re talking specifically about credit unions, let’s discuss the monetary side of this investment first.
For an individual credit union, the cost of building a data warehouse or data lake for an analytics platform starts at around $500,000 at the low end. Most data warehouses and data lakes run well over the million-dollar mark. While it’s certainly a worthwhile investment, it can also be prohibitively expensive for smaller, more community-focused credit unions.
The second major cost factor is time, though we could also say that it costs patience as well. Regardless of the size of the warehouse and the experience of the people putting it together, building a data warehouse takes an average of two or three years. If you want an analytics platform immediately, then creating one in-house from the ground up might not be your best option.
Upkeep and Expertise for Your Analytics Platform
The costs associated with building a data warehouse don’t stop after the three years and one million dollars invested (give or take). Unfortunately, that’s just the price tag for a data warehouse that sits around and does nothing.
To get any sort of utility from your data warehouse or data lake, you need a team of experts to maintain and interpret the data. Per data warehouse, we usually see a need for an average of two or three full-time employees the provide ongoing support. Without a strong team of data scientists, the information is little more than an expensive paperweight or an exercise in useless extravagance.
One of the perks to building a data warehouse is that you can share that data with other financial institutions. Sharing data to facilitate collaborative analytics is one of the best resources available to credit unions on the market.
Data pooling is a convenient way of leveraging your neighbor’s data to augment your strategy. However, every credit union has its own vernacular and ontology, so not all definitions mesh with other credit unions. The power of credit union collaboration is limited unless you take time and make it a priority to learn to share.
The Best Solution
The best solution depends on who’s asking. For massive credit unions with near-limitless resources, building a data warehouse on your own may make the most sense.
For smaller credit unions or those who don’t have a few years to sink into development, there are services that offer all the benefits of data lakes, data warehousing, and data pooling at a fraction of what it would cost to build in-house. These services also have robust support communities that make troubleshooting a breeze.