There is no AI Strategy without a Data Strategy. You’ve probably heard this before, but what does it really mean to have a Data Strategy that supports your AI desires? AI is only good as the data it has access to, so in this session, I will explore the comprehensive process for getting your data ready for AI to use. I’ll look at everything from strategies for ingesting, transforming, storing and exposing your data so that your AI can be the best it can be. You will learn strategies for capturing diverse data sources and ensuring data quality. We will delve into data transformation techniques, highlighting how to clean, normalize, and enrich raw data for optimal AI performance. I will look at various storage options, focusing on scalability, security, accessibility and organizational fit to meet the demands of your AI workloads and we will also cover aspects of data that are more AI specific like managing the semantic layer, emphasizing its role in structuring data meaningfully for AI consumption. Finally, participants will discover methods to expose prepared data to AI applications, enabling seamless integration and unlocking actionable insights. This session is designed for data engineers, architects, and AI practitioners seeking to build robust, AI-ready data pipelines.

You will learn:

• Why data is so important in support of good AI implementations
• The major phases of data preparation
• The unique aspects to apply to data to make it AI ready