Tackling Data Deluge with DQM

Situation

A recognized brand in sports retail experienced a data explosion following the expansion into mobile apps and websites. Their traditional, manual data integrity checks couldn’t keep up, causing costly delays and undermining critical business decisions.

Challenge

The retailer grappled with:

• Increased data complexity, driven by surging digital channel activity.
• Ineffective quality checks, struggling with issues like incomplete data, duplication, and file corruption.
• Manual processes that slowed ingestion and monitoring, amplifying error risks.
• Compromised decision-making, as undetected data issues skewed insights critical to strategy.

The bank’s data challenges stalled progress and stifled the ability to innovate rapidly.

Approach

Mu Sigma introduced an AI-powered Data Quality Management (DQM) system, delivering precision and agility:

• Automated data integrity checks with advanced forecasting and anomaly detection.
• Built prediction intervals for KPIs using best-fit AI models.
• Established real-time exception systems to notify stakeholders of anomalies and expedite corrective actions.
• Designed visualized exception reports for intuitive and immediate understanding.

Mu Sigma’s work replaced reactive processes with proactive, automated monitoring and ensured decision-making accuracy.

Impact

• 65% improvement in operational efficiency, empowering smarter, faster decisions.
• 300 data issues resolved within the first 12 months.
• Significant reduction in data reruns, saving weeks of operational effort.