9 Things to Know Before Your Organization Begins Health Data Science Projects

Artificial intelligence (AI), machine learning (ML), and other related technologies are quickly becoming prevalent tools in the healthcare industry.

With ground-breaking advancements announced almost every other minute and thousands of organizations competing for a piece of the market, healthcare companies are busy keeping up with the latest offerings and high-tech tools.

Choosing the right vendor can be very difficult when working on a new health data science project. It can be even more challenging in an overcrowded marketplace. However, integrating data science into a workflow or operations requires more than procuring data science tools/infrastructure. Data science isn’t something that can be introduced in a business without serious thought into why it is being used. Instead, organizations must integrate data science carefully in a calculated and measurable way.

This article will discuss the top 9 things you need to know before your organization embarks on your data science journey.

1. Build a Highly Collaborative Team of Data Professionals

Subject matter experts, data engineers, architects, and scientists should all work together. Hire smartly, and choose complementary expertise. Coordinate with gatekeepers early.

2. Focus on the Right Business Case

Ask yourself what you want to achieve at the end of this project. Unfortunately, many organizations start data science projects without a clear understanding of the issues they’re trying to solve and if they can even solve them with their current resources.