By itself, predictive modeling can be difficult to implement. What's more, the growing number of data types and sources are making the data preparation process more complex. While predictive modeling can deliver substantial business gains, it can also wreak havoc if the data used for analysis is not accurate or complete.
In this session, we will walk you through the steps to build the right dataset for more accurate predictive modeling. You’ll learn how to:
Assess the quality of your data
Cleanse and prepare data for analysis
Decide what predictive modeling techniques to use for your specific situation
Join the webinar to get practical advice on making data preparation and predictive analytics more accessible throughout your organization.