Cybersecurity and IT

Data Driven Decision Making with Analytics

Many organisations collect substantial data and continue to decide on instinct, not because the data is unavailable but because it arrives too late, in a form nobody can act on, and without anybody having asked what decision it was meant to inform. This course closes that gap. Delegates work through starting from the decision rather than the dataset, defining the question precisely enough to be answerable, and judging whether the available data can actually answer it. Basic statistical literacy is covered: variation, sample size, and why a difference may be noise. Correlation and causation are treated with real examples of expensive confusion between them. Dashboards and the reporting cadence that matches the decision follow. The course closes on acting under uncertainty and on deciding when more data is not worth waiting for.