Every data analyst has a horror story to tell about custom integrations.
And you don’t need to be technical to know that trying to fit a square peg in a round hole is frustrating as can be. Most of us first learned this as small children, playing with building blocks, literally trying to fit a square peg into a place where it just doesn’t. You can push and twist and try to jam it in there all you like, but what you’re too young to realize at the time is that it’s just not compatible.
So what do you do? Well, it depends on how your brain works. The logical thinkers likely stopped and looked around for the square hole where that peg fit. The future engineers probably got a knife from the kitchen drawer and cut away at the hole to make them fit. The frustrated kids probably threw the toys down and walked away entirely.
It’s Wildly Inefficient
The moral of the story is that trying to fit things together that are incompatible is a frustrating, time consuming process, and in the grown up world it can be outrageously expensive to boot. In our world of data management, we’ve found that clients are looking to make things that would otherwise be incompatible fit together on a regular basis, because they have no other choice. They’re often trying to create integrations in platforms that simply aren’t built for them, and they’re trying just about everything to make that square peg fit into that round hole (Excel sheets, anyone?).
Many of the leading data analytics platforms today are capable of incorporating integrations into your existing tech stack. The trouble is that:
- It’s not easy – integrating one single component into a data warehouse that “doesn’t play nice,” is one of the biggest headache situations we hear from data analysts and CTOs.
- It’s not cheap – to create a custom integration, the price tag can often stretch into six-figures. We’ve heard this many times.
- It’s not fast – does 1 to 2 years sound acceptable to you? Not us, either. But this is a realistic timeline for the vast majority of data analytics providers.
Unsurprisingly, custom integrations are often out of the question for credit unions and community banks. Your standard data analytics provider is often doing their integrations piecemeal – one at a time, and at a snail’s pace. It may even take an entire team several months to get through making a small change. It’s also not cheap. Some of these companies will charge a significant price tag for just a single change, and any further changes mean a longer waiting period and a higher price tag, often in the realm of six figures.
A lot of this is simply accepted, because financial institutions aren’t used to working with a tool that’s built to handle integrations.
The Most Flexible Option Available
That’s why we’ve built Gemineye to be the most flexible tool on the market. We’re happy to shape the tool to meet your needs, with whatever integrations you require. Seriously. We won’t piecemeal it, either. We’re used to rolling up our sleeves and adapting the tool however you need to make sure that it works with you.
The best part is that these integrations won’t cost you significantly in dollars or in time delays. Because we’ve built the tool to handle integrations easily, it doesn’t take a huge team to make it work, and we can implement those integrations in a matter of days. So what are you waiting for? Contact us for a non-salesy consultation today.
