<ul><li>Different team structures and skill requirements impact an organization's ability to leverage Data and AI effectively.</li><li>An analogy is used to explain the evolution of data teams from Centralised to Platform Mesh.</li><li>Central teams handle numerous responsibilities requiring focus on key use cases and leveraging tools.</li><li>Expanding a team can increase output, but modern approaches can be more effective.</li><li>The Hub-and-Spoke structure allows for decentralization, catering to medium-sized or tech-first organizations.</li><li>Analytics engineers and data analysts take on more responsibilities in the evolving landscape.</li><li>Challenges arise from data modeling principles, leading to model sprawl and increased costs.</li><li>Hub and Spoke models must have clear responsibilities, ensuring visibility and collaboration.</li><li>Data Mesh approach encourages collaboration and seamlessness, requiring a high level of technical proficiency.</li><li>Implementing a unified control plane can enhance collaboration and orchestration across different teams.</li></ul>

Platform-Mesh, Hub and Spoke, and Centralised | 3 Types of data team

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