Retailers glimpse future with data visualization

Analytics leader SAS has long promised customers “the power to know” and now a major enhancement to data visualization capabilities means retailers don’t have to be a Ph.D to do things faster and more effectively with their massive volumes of data.

It doesn’t hurt to have a data scientist on staff, as a study from SAS and MIT Sloan Management Review shows organization with a top data executive are more likely to have an effective strategy, but visualization is all about making it easier for the regular folks in an organization to work and develop strategies from data.

Accordingly, SAS unveiled a major upgrade to its visual data exploration software called SAS Visual Analytics and its predictive modeling software called SAS Visual Statistics that merges self-service data exploration and reporting with advanced analytics. In essence, business users and data scientists will be better able to collaborate.

“The new releases reflect the converging needs of business professionals and data scientists, as both sets of users seek to boost their productivity,” said Wayne Thompson, SAS chief data scientist. Some business analysts want to go beyond descriptive analytics and do more with predictive analytics. SAS provides an easy way to look into the future.”

The big reveal was announced on April 27 at the SAS annual Global Executive Forum and User Conference. Nearly 5,000 people came to Dallas for the three day event now in its 40th year. “We need to solve more complex problems than ever before,” SAS CEO Dr. James Goodnight told attendees Sunday night in reference to the unprecedented speed at which massive volumes of data are being created. “We never have and we never will stop innovating.”

For example, and not to get overly technical, SAS Visual Statistics adds even deeper statistical analysis to existing SAS Visual Analytics capabilities. Accessed through SAS Visual Analytics’ web-based, intuitive interface, the advanced tools solve difficult problems faster for better business decisions, according to the company. Data scientists can still use SAS Visual Analytics to visualize and disseminate information across an enterprise.

However, data scientists speak their own language and SAS analytics are designed to help the data talk back to them. For example, multiple users can concurrently analyze complex data on Hadoop clusters, relational database systems or SAS servers, build a regression model and then superimpose the predictions onto a geographic map with a few clicks. Business users don’t need to know what Hadoop is (an open source software framework named after the creator’s son’s toy elephant) or how to build a regression model.

Their biggest objective is to glean insights from the data to develop business strategies and drive sales. Data scientists can create models in SAS Visual Statistics and explore the predicted outputs in a variety of visualizations in SAS Visual Analytics, including predictive visualizations. The interactive elements in SAS Visual Analytics now extend to Excel, PowerPoint and Microsoft Office products, enabling better storytelling with data.