I’ve been blogging for about a year about the power of misinformation and our obligations as data professionals to combat it. In a March 2021 blog post, titled “The Power of Misinformation,” I outlined some of our biological instincts that make us susceptible to misinformation and how tricksters exploit them.

Doing more of the work you want, rather than must, is always the dream. And it’s just plain good business. However, many financial professionals feel that they get bogged down trying to find and connect data, rather than focusing on strategic insights.

Time is Money, they say. And when you waste time on onerous menial tasks instead of improvements, you aren’t spending your time, or money, wisely. When it comes to planning and analysis, the role of financial professionals is to provide insights that helps shape the direction of the entire organization. However, many financial professionals feel that they spend too much time trying to find and connect data, rather than focusing on strategic insights.

When businesses begin applying machine learning (ML) workflows to their use cases, it’s typically a manual and iterative process—each step in the ML workflow is executed until a suitably trained ML model is deployed to production.