The relationship between core business function units and IT can often be fraught. The two sides tend to use different vocabulary, and if IT resources are stretched thin (often the case), IT will have to prioritize day-to-day management (putting out fires) over new launches and releases. If those releases contain elements that are holding back the core business units, ineffectiveness and resentment can result.
There is an emerging trend that is helping to solve this issue, though.
The Rise of No-code Platforms
We live in a platform-driven economy now, but the need for more and more internally-designed enterprise options wears IT departments down when it comes to business changes. In response to this conundrum, a new class of apps that can best be defined as “no-code” (or at worst, low-code) have emerged. As the name implies, they can be used without extensive technical knowledge — and as a result, they can be tested and implemented much faster (often days as compared to months).
Rather than starting a new project by hard-coding, you typically work within a visual development environment that comes together across four main aspects:
- Data models: Define how and where the data is stored, and how that data is processed within the system.
- External data: Integrate third-party sources. Frontrunners in no-code are drawing from increasing ability to integrate with SOAP web services and REST APIs to present visual integration connectors.
- Business logic: Orchestrate data using visual workflows.
- Interface: Visually manage the user interface of internal and customer-facing applications.
Obviously, no or low code will save time and get business-critical programs to those departments when they need them, but what are the other benefits?
How Data Science Intersects Here
It’s been said that data is potentially the new oil. One of the interesting parallels there is that when we first truly scaled with oil, we needed mid-stream systems in place to effectively move it from source to end user. The same is now happening with data. Companies are getting smarter about assembling data teams or leadership units, but the way they interact with and analyze data might not resonate (in terms of vocabulary, etc.) with the senior business decision-makers.
To solve this issue, you need data translators — people who reside between the science side and the executive side. But again, the biggest challenges to hiring for or developing such a role are time constraints and business priority. Switching to low-code or no-code in your firm makes sense because it frees up time. That time can be used in a more practical process for taking the data being captured and turning it into effective, revenue-driven decision-making.
Looking for a better way to operationalize your models?