Rethinking Data Analytics in the Age of AI

From Raw Data to Actionable Insights, What's Changing and What Still Matters.

Most analytics teams today sit on top of large volumes of data collected from different systems, departments, and tools. They build self-serve dashboards and generate custom reports for stakeholders. They spend hours writing SQL queries and developing predictive models to answer ad-hoc business questions. Yet despite all this effort, when it’s time to make a key business decision, the data is often late, incomplete, or left out of the conversation altogether.

This brings up a realistic set of questions. Can AI meaningfully reshape how analytics teams operate? Will it automate part of the work analysts do today or simply change what analysts spend time on? And if AI shifts how the work gets done, should analytics still be seen as a support function or something closer to a strategic partner?

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1. The Journey From Analytics Ready Data to Business Value Creation