Big data has become a critical ingredient for business intelligence. Once you translate that massive amount of information into meaningful insights, it can help you spot trends, identify new opportunities, and make better decisions for your business.
To help, you may want to engage a data scientist—a professional who has the skills and curiosity needed to explore, analyze, model, and explain what the numbers mean.
“Data agility, the ability to understand data in context and take business action, is the source of competitive advantage not simply having a large data lake.” — Thor Olavsrud, Senior Writer for CIO
Often coming from a background of statistics or analysis, data scientists also have the technical skills needed to create sense from multiple data inputs. As explained in “The Tools of Big Data Science,” they have a lot at their disposal to help mine and report on that information, such as:
- Programming languages
- Analytics programs
- Database management systems
- File system computing tools
- A/B testing platforms
Data scientists also make use of data visualization tools, applying different types of graphics—from basic pie charts and scatter plots to interactive maps—to help explain complex ideas, more easily spot patterns, and bring a fresh perspective.
New tools help bridge the skills gap
As important as data science has become, not everyone has ready access to such expertise. An MIT Sloan Management Review survey in 2015 found four in 10 businesses had a “lack of appropriate analytical skills”—and the competition for talent has only become tighter.
In the wake of that gap, new tools have emerged to absorb some of the heavy lifting and make data visualization more accessible for experts and lay-people alike. “19 Tools for Data Visualization Projects” lists some of the most popular out-of-the-box tools—broken down by use case—including Tableau, one of the most popular options.
Tableau expertise is one of the hottest skills, ranking third in the Q4 2016 Skills Index as companies seek help migrating their data, creating tailored dashboards, and learning to use the program.