Best Practices for Analyzing and Reporting on Business Data

• Overview
• Credits

Make sound business decisions with advanced science data. Understand the necessary steps you must take in order to begin with predictive analytics. Predictive analytics and data science have become go-to approaches to advanced analytics analyses and decision making with organizations. However, many organizations have little to no experience with these techniques within their organization to build predictive models or assess capabilities of consultants or potential hires. This topic helps the persons responsible for defining your predictive analytics strategy understand the key steps and considerations for typical predictive analytics projects without resorting to buzz-words. High-level concepts and some deep-dive ideas will be explained in ways that business stakeholders and analysts can understand.

Authors

Agenda

Have a Framework for the Project

• Defining Predictive Analytics

• Introduction to CRISP-DM

Select the Right Problem to Solve

• How to Choose the Target Variable

• Principles in Selecting the Data

Don't Skimp on Data Preparation

• Big 3 Data Prep Steps

• Principles of Feature Creation

Know the Strengths and Weaknesses of Algorithms

• The Big 3 Algorithms

• What to Believe and Distrust About Predictive Models

Assess Your Models With the Right Metric

Conclusion and Summary

Additional Formats