WALLDORF, Germany, April 3, 2012 /PRNewswire/ -- As organizations evolve their business strategies to remain competitive in ever-changing markets, they rely on today's information to make choices for tomorrow. Empowering them with the ability to improve decision-making by predicting future outcomes, SAP AG (NYSE: SAP) today announced SAP® BusinessObjects™ Predictive Analysis software. The new offering aims to equip more people with a modern, user-friendly, graphically stunning tool for predictive modeling and advanced visualization. The software is intended to harness and unleash the full value of "Big Data" when coupled with the power and speed of the SAP HANA® platform, enabling organizations to reveal and act upon untapped opportunities and hidden risks.
"There is a lot of untapped insight that could be exposed from exploding internal and external, structured and unstructured data sources," said Dan Vesset, vice president, Business Analytics solutions, IDC. "Predictive capabilities help businesses explore and identify the opportunities and risks hiding in the sea of all that big data. SAP's integrated approach to predictive analytics helps more users learn not only what has happened, but also understand why it happened, what might happen and what the best course of action is."Predictive modeling has traditionally been the domain of statisticians and data scientists. However, the intuitive interface and stunning visualization of SAP BusinessObjects Predictive Analysis are intended to bring predictive insight to an under-served user community – the business analyst. With the software, analysts can create models either by using the predictive algorithms included or can integrate and use algorithms from the widely-used R open-source data analysis and statistical language. SAP plans to enable customers to use the software for instant insight into large data volumes to anticipate future opportunities and risks. Examples include:
- Understanding how historical sales, costs and other key metrics translate to future performance
- Seeing how predicted results compare with goals
- Revealing the causes of customer satisfaction and employee turnover
- Showing how past and emerging trends impact the bottom line
- Finding correlations in data for cross-sell and up-sell opportunities
- Locating anomalies and clusters for targeted analysis