Few business decisions stand to have a greater impact on success than hiring the right people for the right roles. Predictive analytics is bringing data-driven intelligence to the hiring process.
Find out how to provide the answers decision makers throughout your organization need to reduce costs, operate more efficiently and increase the bottom line.
Predictive analytics techniques can help businesses not only spot fraudulent transactions, but also identify deceptive vendor networks.
Chat with subject matter experts on the challenges of fraud and how predictive analytics can help you detect suspicious behavior before it harms your business.
You can't afford to lose your hard-won customers. Join us for this CrowdChat on May 10 to learn how predictive analytics helps businesses use big data to drive customer retention and target marketing efforts more precisely.
Many data scientists are using the “Cross-validation Method” which is not supported in SPSS Modeler without a little extra work. The objective of this article is to describe a way in which one can implement the “Cross-validation Method” in SPSS Modeler.
Check out this example of Python scripting in terms of SQL optimization. When retrieving data from a database, one may want to limit data to a certain amount of dates. Learn how to select data relative to the current date when the stream is executed.
Together with IBM SPSS Modeler and Teradata Aster NCLuster_loader, Houston Analytics Accelerator forms a package that is faster than the SPSS+ODBC method to insert plenty of data to a database, and much easier to use than the NCluster_loader. Accelerator makes data uploading to the Teradata Aster platforms so easy that anyone can do it.
Leading companies are thinking beyond Big Data, and using Big Text Analytics to create a more comprehensive, intelligent customer analysis. Businesses can enrich Big Data with Big Text to develop a better understanding of customers, and as a result, create better business outcomes.
We highlighted some powerful quick wins you can achieve using IBM SPSS Modeler to solve key business problems such as reducing churn with a churn model.