Sancus: Data Quality Management by Tredence

Retail and consumer goods manufacturers are turning to real-time data to address evolving customer needs, forecast fluctuations in demand and mitigate out-of-stock risks. The challenge in moving to real-time analytics powered by AI and ML is that low-quality data compromises the impact of advanced analytics. To address data quality issues, Tredence developed Sancus, an AI and ML data quality management solution, which improves data quality by cleansing, enriching and presenting data on an interactive dashboard with configurable data quality metrics. Together, Tredence Sancus and Databricks Lakehouse for Retail deliver real-time insights built off clean data to drive customer engagement and improve supply chain efficiency. Now you can:

• Ingest, harmonize and enrich source data with multiple external data sources to gain a holistic view of customers across all omnichannel touchpoints in real time
• Solve diverse data quality problems not addressed by traditional rule-based or fuzzy matching solutions to empower data-driven decision-making
• Use a centralized data quality dashboard, integrated with automatic alerts, to help customers track metrics across sources in a single place and enable AI and ML adoption