Anna Brown, Editor, Business Analytics Knowledge Exchange

We all make decisions on the fly. What will I eat for breakfast? Will I have one or two shots of espresso in my latte? What will be the first project I tackle today? We make these trite daily decisions very quickly, without applying too much thought or assessing too many options.

But what about the decisions made that are critical to your business? What about those that need to take into account amassed variables and weigh heavily against innumerable ‘what if’ scenarios? More organizations are turning to data – and analytic – visualization to:

1. Show a complete picture of their business (data)
2. Ask more and better questions (analytics)
3. Make faster, more effective decisions.

Same process, smarter questions
As businesses embrace visual means to discover interesting patterns within data, they should consider where visualization takes place along the entire analytics process. Consider the predictive analytics process shown by independent research firm Forrester Research, Inc., in the report, “The Forrester Wave: Big Data Predictive Analytics Solutions, Q1, 2013” (Figure 1), and referenced in a previous SAS Voices post on the firm’s big data recommendations.

This cycle outlines the cyclical predictive analytics process, underscored by the business goal every step of the way. Multiple organizations (business, IT, statistics groups, etc.) interact in this process from understanding the problem, to preparing, collecting and exploring the data through to building models.

Analytic visualization – or SAS® Visual Analytics – limits the number of these interactions by allowing business analysts to ask questions and get answers at the “prepare data” stage. Without burdening IT, business managers can combine and explore data and ask smart questions using their business or domain expertise. They can then present and evaluate the answers.

As a result, the predictive analytics process can run again and again with better and more precise questions. And IT can focus on other parts of the process rather than constantly stopping to pull reports for business units.

Sound efficient and valuable? Learn more about SAS Visual Analytics and see for yourself.