An important ingredient for any successful business is its staff. And yet recent research shows that human resources ranks lowest among front office operations when it comes to using predictive analytics, particularly to recruit and retain the right professionals for the right positions. But that
Smart predictions can spell the difference between whether your company succeeds wildly or falls by the wayside. Get the details on four strategic pillars for smart, proactive business through predictive analytics deployment in a series of new blog perspectives.
The craft of data science demands expert judgment every step of the way. See how data scientists can adopt a standard data science methodology that can harmonize steps among diversified teams for applying core concepts of data science, analytics and data management in the data science lifecycle.
SPSS Modeler was the star of its own ring at IBM Insight 2015. Take a look at what attendees learned about the latest and greatest capabilities of Modeler to see how Modeler can help your organization find its place in the insight economy.
IBM Insight 2015, officially taking place over five, jam-paced days, 25–29 October 2015, in Las Vegas, Nevada, can actually be an even longer event for IBM Business Partners. Take a glimpse at some of the great content around IBM SPSS Modeler and its innovative implementation in Insight 2015
At IBM Insight 2015, you’ll be able to discover the latest and greatest in the SPSS universe. A lot will be going on at Insight, so take care not to miss the sessions that will interest you most. Learn the ins and outs of SPSS sessions at Insight, allowing you to make the most of your Insight
Text mining is the next step in data mining, offering advanced capabilities for extracting meaning from vast, amorphous masses of data. Despite its complexity, text mining has much to offer businesses—and the list is growing. Discover what text mining could mean for your organization today.
Advanced predictive analytics requires data preparation strategies that can transform the data, enriching it to make it suitable for processing. Indeed, your choice of data preparation strategy can help you boost the accuracy of the outcomes you achieve.
Don’t find yourself falling prey to pitfalls when you implement a predictive analytics solution for your organization. Discover what mistakes to avoid when planning your implementation and setting strategy.
Inaccurate perceptions of predictive analytics are common in the business world. In reality, predictive analytics is straightforward to understand, can leverage existing skillsets in business and IT organizations, and can deliver value in most industries and lines of business. Getting started with
High-quality predictive analytics, statistical modeling and data mining tools are the heart of a well-run modern organization. Organizations of all sizes, in all sectors and geographies, are using these tools to drive evidence-based predictions into the full range of business processes, operations
Prioritizing data mining projects is a delicate art, equivalent to the decisions that R&D managers face every single day. How should you prioritize your data mining efforts and allocate your limited resources most effectively? Most important, how do you decide what NOT to work on?