Why Enterprises Need Data Quality & Observability at Scale

Researchers found that improving data quality and usability by 10% could increase return on equity (ROE) for Fortune 1000 companies by 16%. To achieve this, enterprise data teams need a data observability solution with advanced AI/ML capabilities to automatically detect data and schema drift, anomalies, as well as lineage. Data observability offers full traceability of how data transforms across the entire data lifecycle, helping predict, prevent, and resolve unexpected data downtime or integrity problems. Acceldata Torch is a multi-dimensional data observability solution that provides a single unified view of the entire data pipeline across different technologies throughout the entire data lifecycle. It can help ensure data reliability even after the data transforms multiple times across several different technologies and automatically identify anomalies, root causes, and classify large sets of uncategorized data. AI and ML capabilities are crucial for enterprises to improve data quality at scale as manual interventions alone aren't sufficient.

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