Business intelligence

Graded Discussion: Techniques for Predictive Modeling
When we think about various techniques for predictive modeling, always remember that the realm of predictive analytics is the use of data which is supported with various statistical algorithms and even machine learning techniques. When properly used, these methods and techniques can be used to identify the probability of future outcomes based on historical data.
When an organization needs to use predictive modeling or analytic techniques, they have many tools to consider and some include the following not limited to:
SAS Predictive Analytics (https://www.sas.com/en_us/insights/analytics/predictive-analytics.html)
IBM Predictive Analytics (https://reviews.financesonline.com/p/ibm-predictive-analytics/)
SAP Predictive Analytics (https://searchsap.techtarget.com/definition/SAP-Predictive-Analytics)
Rapid Miner Predictive Analytics (https://rapidminer.com/resource/operationalize-predictive-analytics/)
Altair Predictive Analytics (https://www.datawatch.com/in-action/angoss/)
Any many others
Using the list of predictive analytic tools listed above or using others of choice, compare at least three or more of these tools based on research and or experience and share with the class which you would prefer any why?
 
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1. What recent factors have increased the popularity of data mining?

2. What are the key differences between the major data mining methods?

3. Is data mining a new discipline? Explain.