Successful predictive analytic projects follow a well-defined approach from requirements to modeling, implementation and deployment, embedding the analytic results in operational systems that improve business performance.
In this live webinar, James Taylor, CEO and Principal Consultant at Decision Management Solutions and Matt Kitching, Senior Data Scientist at Apption, an award winning analytics consulting company, discuss the business value of predictive analytics and show how decision modeling adds value throughout Apption’s big data analytics workflow. Using a recent Apption Customer Retention Analytics engagement, James and Matt walk through the workflow and show the value of decision modeling in each step:
- Big Data Analytics allows you to use all your data to make key business decisions.
- Decision modeling aligns analytics requirements with key business measures, creating a shared understanding across stakeholders while providing structure and transparency, promoting buy-in.
- Decision modeling focuses data scientists on the most relevant data, streamlining data preparation and exploration.
- Predictive Analytics provide you with actionable insights that help you solve existing problems or head them off.
- Decision modeling provides a framework to evaluate and refine predictive models to ensure they will have a business impact.
- Decision modeling ensures that predictive analytic models can and will be successfully deployed.
Predictive analytics are increasingly a must-have competitive tool. A well-defined workflow and effective decision modeling approach ensures that the right predictive analytic models get built and deployed.