Getting Real About Big Data Talent

One of the biggest misconceptions business leaders have about data scientists is this: They have some sort of mysterious, magic formula to extract meaningful insights and solve all of their organization’s problems…If I had a dollar for each time I’ve had to remind clients that there is no one secret formula, I would be a rich man! Here’s the reality:

A means to an End

Data mining alone isn’t enough to move a business forward. It’s what you do with that information that counts. “There’s an expectation that collecting large quantities of data will make an organization smarter,” says Mark Schwarz, VP of Data Science at Square Root. “In reality, that often leads to decision paralysis and the inability to actually move the needle within the business.”

Quantity ≠ Quality

Brian Lange, data scientist at Datascope Analytics, says that while they can make better predictions with more data at their disposal than ever before, data scientists aren’t immune to the pitfalls that comes with making predictions. “Overfitting (the statistics equivalent of missing the forest for the trees), false assumptions, sample bias- these are all things that aren’t solved by the quantity of data you throw at the problem,” he says. So what should companies do instead? “They should be focused on uncovering the right information.”

Asking the Right Questions

I’ve found the key to leveraging Big Data is having creativity and insight to ask the right questions that are unique to each business model. “Many data scientists understand the process of analyzing and finding commonalities in data, but they don’t have the necessary business context to determine which commonalities or anomalies can actually help the business,” says David Giannetto, author of Big Social Mobile.

Any average expert can pull data based on factors handed to them, but the truly valuable ones have the skills to proactively focus on information that will actually change behavior-and that is the type of talent I look for!