Boosting the power and value of data with predictive analytics

Chief Statistician and Distinguished Engineer, IBM Predictive Analytics, IBM

You’re probably familiar with some impressive predictive analytics success stories. But how does predictive analytics actually work? Watch this one-minute video to get a quick overview.

If you’ve seen the video, you know that predictive modeling takes historical and existing data and uses it to provide a clearer view of current conditions and to forecast the future.

Organizations achieve desired outcomes with predictive analytics by using proven statistical algorithm techniques. While you don’t need to know what they are, it does help to understand the process.

What’s the optimum predictive analytics process? First, it’s important to define the business problem. For example, you want to determine if a certain customer is a good or bad credit risk. Once you know this problem, you determine whether you have the right data. The data has to be relevant to your business problem, and it can come in a number of forms. We can help you determine your data's relevancy. sufficient historical data on both good and bad customers that covers all kinds of characteristics, such as delayed payment history and customer longevity, you can define profiles for good and bad credit risks. This data is then applied to the algorithms to find a pattern or a model.

Next, you need very rich software with a range of capabilities. Even when seeking answers to a single question, the optimum software lets you apply the data to multiple algorithms. Finally, be sure your analytics software can:

  • Determine the quality of your data
  • Suggest which algorithms might be best in terms of getting answers related to your business question
  • Run the numbers and present results in human terms and concepts

That’s the basic process. If you’re looking for a simple methodology, we can help you use your own data, and the analytics will highlight the outcomes in easily understandable ways. Or, explore our range of advanced analytics tools such as open source, big data and streaming data.

What is big data analytics? You’re aware that big data is being generated by everything around us: digital processes, transactions, social media exchanges, systems, sensors, mobile devices and more. It comes from numerous sources at an alarming velocity, volume and variety. Big data analytics takes this complex unstructured data, analyzes it, makes fast decisions on massive data volumes and unlocks the value behind it. IBM is here to help you gain big insights with its innovative solutions and support.

We offer a range of solutions, including:

  • IBM SPSS Modeler: This powerful data mining and text analytics tool helps you build accurate predictive models quickly and intuitively without the need for programming.
  • IBM SPSS Analytic Server: Analyze big data to gain predictive insights and build effective business strategies. When IBM SPSS Modeler is combined with IBM SPSS Analytic Server, analysts can develop and deploy predictive analytics over big data without extensive technical skills.

Discover how you can create an interactive analytics environment that connects core business functions with decision-makers and data scientists in the IBM and Ziff-Davis white paper, “Big data, little data and everything in between.”

Get predictive analytics working for you. Contact an IBM expert or visit our predictive analytics website.