One of the many fun things about being head of product at Boomi is that not only do I get to experience and drive the present-day state of data in business, but I get to prognosticate about the future.
I’ve been talking with Mike Veldhuis of Nalta in a four-part podcast series on how to become a data-driven company. In our first and second episodes, we focused on your data and the business reasons behind becoming data driven.
But in the next two episodes (here and here), we talk about where data-driven businesses are headed.
There’s the evolutionary path ahead that connects us from where we are today, generating massive quantities of data, to the future, where we’ll be even more interconnected with even more data.
Moving forward, emerging data-driven technologies like blockchain, AI, and machine learning (ML) have the capacity to completely upend the business applications of data integration and data connectivity in the enterprise.
Take the combination of AI and ML. We’re working with a company called Aible to bring a low-code approach to integrating AI and ML data directly into applications like sales. Early use cases show this can speed adoption of automation technologies because the data is usable and useful immediately. We’ve seen customers succeed in developing new sales models, reconfiguring sales orgs’ focus, or even fine-tuning marketing programs.
And while blockchain certainly gets all the hype, I think we have more promise in the near-term from automation data. Listen to learn why.
In our last podcast, Mike and I get into some use cases that really make us think about the convergence of our data and everyday life. Mike brought in a question from a Dutch colleague in law enforcement asking about how we innovate and take advantage of these amazing new technologies while also protecting citizen privacy.
Take connected car data, for example. This trove of data could be a terrific help to law enforcement tell when a car is speeding or breaking traffic laws, but privacy laws protect the driver, too.
It’s a matter of “do no harm.” And it’s a tough question.
The challenge we all face is how to navigate that grey area to make sure we respect the lines and can put in place checks and balances. And this applies to geographic boundaries as well.
Data sovereignty regulations can vary from country to country, which can inhibit widespread deployment of an integration solution on a global basis. At Boomi, we are currently mapping personally identifiable information (PII) markers into our global deployments to create a gate, if you will, to enable global data connectivity that is customized by location.
It’s an exciting time to be at the forefront of data integration and connectivity.
Tune in here for our last two episodes. Read Ed’s previous blog about these podcasts here.