Thanks to your LMS, CRM, SAP, and other systems, you have large numbers of data points capturing mountains of history. Your LMS can tell you how many people took a class and whether an individual completed it successfully; the relationship between a student and course is hard-wired into the physical database through a standard business rule. Still, an organization’s LMS data almost always contains duplication, compromise, and physical restrictions. When you’re asked to respond to more important questions, these restrictions make it harder to answer, for example, “Did those same class attendees ever apply what they learned to their own performance driving business improvement?” Identifying the right data for the right question requires interesting and complex combinations. Data modeling provides the structure for this data detective work.

 In this workshop, you will learn how to create visual data models capturing not the physical but the logical view of your important data. These models visually document the logical data driving performance goals through metrics that stay bounded in realistic data “scope.” Using these models will help you ask better questions to uncover successful and unsuccessful patterns of learning. This technique helps you graphically represent how data relates to business and uncover the rules of the business that drive investigation.

In this session, you will learn:

• How to build an entity relationship data model for your learning and development (L&D) organization 
• How to uncover important questions regarding the outcomes of learning
• How to communicate about dysfunctional learning through business rules
• How to create realistic and actionable criteria for monitoring and reporting progress

Audience: Designers, developers, project managers, and managers.

Technology discussed in this session: Data systems and processes.