This document discusses how learning and development professionals can become more data-driven. It defines key terms like learning data and analytics. It explores how to collect and analyze different types of data, including learner behavior, assessments, and business outcomes. The document also discusses emerging approaches like machine learning and artificial intelligence. It provides examples of how data can be used to personalize learning, make predictions, and gain insights to improve performance. Overall, the document promotes taking a more experimental and iterative approach to learning design and using data to continuously improve programs and their impact on business metrics.