It is no longer enough to derive insights from historical information. The best reports and dashboards on historical information can only report on what has happened, not what could happen in the future. Predictive analysis supported by data mining techniques enables companies to detect fraud, predict customer behavior, market outcomes and forecast demand for products and services. This can easily be accomplished by putting data, the newest and most powerful corporate asset, to work.
Models can be built that forecast how customers of a particular demographic, purchasing and repayment history would react 12 months or 24 months out based on the past behavior of customers with similar characteristics. Similarly, companies can determine on Day 1 how much to assess new customers for credit deposits or other financial loss-prevention safeguards instead of applying standard procedures to every customer and having to absorb losses later.
At Kindle Consulting, we have worked with popular data mining tools from SAS and Oracle and are very excited to welcome SAP BusinessObjects Predictive Analysis to the BusinessObjects stack.
SAP BusinessObjects Predictive Analysis is expected to be generally available in late 2012. It is SAP's response to the growing predictive analytics segment of the BI market. SAP BusinessObjects Predictive Analysis, the company's new product, has been shaped by competitive and market forces, including the momentum of open source R, in-memory and in-database processing, and the convergence of analytics with BI. SAP BusinessObjects Predictive Analysis has two components: model development and execution, and data visualization. SAP BusinessObjects Predictive Analysis is well integrated with SAP's BI platform in that the tool can access a Universe (data model) in either the version 3 (.UNV) format or the newer version 4 (.UNX) format.