When it comes to choosing a data analytics solution for your financial institution, the ability to provide flexible and robust integration options should sit at the top of the list. Why? Because data ingestion is the backbone of a successful data analytics program. Integrations provide the data, and when a data analytics platform doesn’t allow – or makes certain critical integrations very difficult – the entire data foundation can collapse like a domino effect. Here at Gemineye, we’ve heard of countless situations where clients and colleagues have been subject to restrictive integration parameters from data analytics providers, including: 1. Flat out inability to perform certain integrations 2. Charging hefty fees for “custom” integrations or integrations not in their wheelhouse 3. Long wait times or delays to implement an integration request In this article, we’ll break down the basics of integrations and provide tips to protect your financial institution. Let’s dive in. Why Integrations are so Important in a Data Platform There are hundreds of vendors that credit unions and community banks use to run their financial institution, and each one plays a critical role in data ingestion. Of course, the heavy hitters include your core, consumer loan and mortgage originations, and digital banking. But as technology becomes more advanced and nuanced, the third-party vendor and custom integration landscape becomes more dense. That, in turn, provides more choices – and more risk for data analytics provides to not accept that your third-party vendor integrations. For example, some data analytics providers have pre-built integrations for Hubspot, but not InMoment. If your financial institution uses InMoment, then you are stuck with the unpleasant decision of either not incorporating this key data into your platform, or switching over your entire CRM. One can quickly see how frustrating and time-consuming this situation can become. The Wild, Inefficient World of Integrations Many of the leading data analytics platforms today are capable of incorporating most integrations into your existing tech stack. The trouble is that: 1. 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. 2. It’s not cheap – to create a custom integration, the price tag can often stretch into six-figures. We’ve heard this many times. 3. 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. 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. Every data analyst has a horror story to tell about integrations. Trying to fit processes together that are incompatible is extremely inefficient, and in 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?) Questions to Ask Before You Choose a Data Analytics Vendor What data sources are the most important for us to have available? What vendors/systems do we consistently struggle to get data from? Have your potential vendors shown competence in the variety of sources they’ve ingested? (Look for 20+ integrations) Can the vendors provide references or case studies regarding their integration successes? How transparent are they about pricing, change orders, and additional fees? Discover More About the Capabilities of the Gemineye Data Lakehouse The Gemineye Data Lakehouse currently supports over 75 integrations – even the ones that other data analytics providers won’t touch. Our integrations incorporate leading credit union and bank solutions, like consumer loan and mortgage originations, digital banking, CRM / MRM, third-party data vendors, and more. We’ve worked hard to develop a robust suite of integrations that are pre-built, meaning less redundant work for your internal team, less implementation time, and a lot more cost-savings.