Ai Data Quality

Problem

Poor data quality was leading to inaccurate AI model predictions, resulting in business decisions based on flawed insights.

Approach

I developed a comprehensive framework for assessing and improving data quality before it entered the AI pipeline, implementing automated checks and validation processes.

Outcome

The framework reduced data errors by 87% and improved model accuracy by 34%, leading to more reliable business insights and better decision-making.

Screenshots & Visuals