In this session, Ian and Sophia, share their experiences and learnings while developing the first data analytics models in their respective organizations. Both faced challenges, including minimal operational data, lack of data governance, and infrastructure issues. However, they eventually put their first models into production by understanding existing infrastructure, leveraging partnerships, maintaining focus on objectives, and hiring the right people.

The speakers emphasized the importance of defining objectives, stating that clear objectives, the right people, and senior leadership support are vital for building a successful data analytics program. Building trust in the data, hiring diverse teams, and investing in people, technology, and processes were also crucial factors for success. The joint effort involved multiple models, collaboration with various business functions, and using Azure's cloud environment for model development. They recommend establishing a development-to-production pipeline as soon as possible and ensuring the Enterprise is prepared for cloud development beforehand. Other essential planning and foundational elements include setting expectations, integrating data, and connecting analytics production systems.

Ultimately, they stressed the importance of adapting to unique organizational needs and overcoming challenges along the way.