Collecting data is the easy part. Collecting intelligent data that is easily read and utilized by AI powered systemsis where it gets tough.

This session provides guidance, starting with collecting data that provides value and structure for current AI systems. No matter how you collect the data—xAPI, cmi5, Google Analytics, others—it can come in fast and furious and quickly get messy. Most of the specifications are easy to implement, i.e., there is not much coding involved, if any at all. Where your time should be spent is planning what you want to collect and how that data will inform your AI systems to improve the output—in other words, creating your data strategy. We will walk through decisions you need to make and how to build a strategy to collect data that your AI systems can use effectively to automate and drive adaptive learning systems. You will actively work through the design of a data strategy during the session

In this session, you will learn to:

• Explain the importance of a data strategy and its role in enabling effective AI systems
• Design a data strategy that supports the development, deployment, and scaling of solutions
• Apply a structured process to implement and manage a successful data strategy for AI initiatives
• Document and communicate a data strategy to ensure alignment, governance, and long-term usability

Participants would benefit from having an understanding of data principles with some baseline on learning data schemas.