Predictive analytics has helped drive business intelligence (BI) towards business performance management (BPM). Traditionally, predictive analytics and models have been used to identify patterns in consumer oriented businesses, such as identifying potential credit risk when issuing credit cards, or analyzing the buying habits of retail consumers. The BI industry has shifted from identifying and comparing data patterns over time (based on batch processing of monthly or weekly data) to providing performance management solutions with right-time data loads in order to allow accurate decision making in real time. Thus, the emergence of predictive analytics within BI has become an extension of general performance management functionality. For organizations to compete in the market place, taking a forward-looking approach is essential. BI can provide the framework for organizations focused on driving their business based on predictive models and other aspects of performance management.
We'll define predictive analytics and identify its different applications inside and outside BI. We'll also look at the components of predictive analytics and its evolution from data mining, and at how they interrelate. Finally, we'll examine the use of predictive analytics and how they can be leveraged to drive performance management.
We'll define predictive analytics and identify its different applications inside and outside BI. We'll also look at the components of predictive analytics and its evolution from data mining, and at how they interrelate. Finally, we'll examine the use of predictive analytics and how they can be leveraged to drive performance management.
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