5 Traits Successful Data Analytics Teams Share

Data is everything these days. It’s the fuel that informs companies’ daily decisions, providing that extra edge over competitors in driving innovation and long-term growth.

But merely collecting and processing data won’t get companies very far. Employing a overall data strategy and leveraging data visualization tools is a great start. However, without the right data analytics team in-house, it’ll be an uphill battle.

Here five crucial traits successful analytic teams possess.

They’re Thorough

Data needs to inform our decisions, we know that much is true, but we shouldn’t trust it blindly. After all, data is collected and assembled with the help of humans, meaning it’s subject to flaws. The right data teams don’t take data for its word. If something looks too good to be true, they dig deeper to uncover the true story.

Additionally, data teams need to be thorough because despite the prior training and education they’ve received, real-world data jobs are a lot messier than looking at data sets in a controlled environment. If a team isn’t willing to roll up their sleeves, then data initiatives will never get off the ground.

They’re Curious

With something as granular and in-depth as data, answers don’t jump out at you, at least, not without a data visualization software. Successful data teams are innately curious. When teams are curious it means they’re engaged with the work; they’ll go deeper to detect issues and develop solutions, even if things look peachy on the surface. These teams have more questions and possess the tenacity to find the answers to those questions.

Practical

Thoroughness and curiosity, as important as they are, can also lead to tunnel vision and spending way too much time on things that won’t deliver business value. Successful data teams have the ability to step back and ask if tackling a problem or creating a solution to something will actually make a difference in terms of business goals.

They’re Balanced

It’s tempting to hire an impressive data professional who seems to have all the skills you need, but it’s unrealistic to expect value out of data without a diverse team assembled. Data analytics takes many roles to execute properly; data scientists, data analysts, data engineers, data curators, data product managers and even a chief data officer all have their purpose on a successful team.

They Understand How Data Relates to Overall Business Goals

As Daniel Mintz writes for InfoWorld, “Good analysis presented poorly is just as useful as bad analysis presented well.”

A technical team that doesn’t fully understand business goals won’t do a good job of presenting useful information. Businesses need their data teams to vet requests and initiatives as worthwhile to the business or not, since they’re the only ones close enough to the data to truly know. When reports and findings are communicated, the team must have the ability to present insights free of jargon so the rest of the company can understand.

Of course, a great substitute for a full-fledged data analytics team is to use an intelligent search-driven analytics and data visualization software that can answer employees’ most pressing questions in seconds.

Learn more about what data analytics with ThoughtSpot can do for your business today!