It’s Time to Refocus on Data Science and Data Analytics

The coming year is the perfect time to refocus your data science and data analytics efforts to increase revenues and drive core efficiencies.
Multiple times a week, I am contacted by a software startup promising a new platform that will allow me to leverage AI to solve my business challenges and harness new opportunities. Sound familiar? Is this evidence that AI is at peak hype in everyday companies, or is it simply that many companies still struggle to deploy analytics and data science solutions with real bottom-line impact to their business?
Companies know they should be investing in artificial intelligence and many have spent millions of dollars with no tangible results. Often, under pressure to demonstrate they are investing in “future technology” and not just the same old legacy platforms, enterprises carve out significant funding and spin up data science teams. Unfortunately, these teams often lack connection to the complex dynamics of the business and the projects they tackle do not yield a true ROI. A desire for quick wins can lead data science practitioners to analyze “low-hanging fruit” and, unfortunately, miss out on opportunities for larger business impact.
With signs of economic slowdown and increasing margin pressures across many industries, 2020 will be a year we see companies refocus their data science and data analytics efforts to increase revenues and drive core efficiencies. I can see two big trends emerge from this:
Data visualization has been a red-hot trend for several years, and luckily for us, business intelligence tools continue to improve. Most platforms now have open marketplaces that offer industry-specific utilities to data analysis professionals. As wider audiences of non-data business leaders show interest in data science applications, the use of data visualization to pitch business cases will become more critical. Data visualization and business intelligence tools have been a focus area of my organization’s technology learning efforts for this reason.


