Credit unions can benefit significantly from collecting and storing information to leverage Big Data. The cost of building a data warehouse is one of the challenges of applying Big Data and Analytics. If you’re considering building a data warehouse for your credit union, it’s essential to know the costs and on-going upkeep involved.
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 on-going support and upkeep costs.
Here are a couple of common issues associated with building a data warehouse for the credit union industry.
Data Warehouse Pricing for Credit Union Analytics: What to Consider
Initial Investment Costs
There are two primary expense considerations for any enterprising credit union looking to construct its 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 this investment’s monetary side 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. Regardless of the warehouse’s size 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 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 to provide on-going support. Without a strong team of data scientists, the information is little more than an expensive paperweight or an exercise in useless extravagance.
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, some services offer all the benefits of data lakes, data warehousing, and data pooling at a fraction of the cost to build in-house. These services also have robust support communities that make troubleshooting a breeze.