Part 10/13:
He argued that effective data governance must prioritize cataloging, lineage, and what he called "validity"—ensuring that data can be trusted as a true representation of reality. Without these controls, organizations risk making decisions based on unreliable data, especially critical in AI applications where data quality directly impacts model performance.
The Future of Cloud and AI: A Rapidly Evolving Landscape
Looking ahead—whether in two months or five years—the expert acknowledged the difficulty in predicting technological trajectories. The pace of innovation driven by Moore's Law and rapid API developments makes forecasting challenging.