About
At DataResults, we develop intelligent, scalable, and fully customizable data quality engines capable of operating efficiently in Azure and AWS environments, integrating with leading modern data architectures. These engines act as pillars of governance, applying technical and business validations at each stage of the data journey—from ingestion to consumption—based on dynamic and customizable rules for different domains and sources. How they work: Customizable rules: Our engines use catalogs of quality rules (precision, completeness, consistency, uniqueness, relevance, integrity) that can be defined by domain, table, field, or specific business rule, with easy maintenance via JSON files or configuration interfaces. Multi-cloud execution: With native support for Azure Data Lake, Azure Databricks, AWS S3, AWS Glue, and Spark, the engines adapt to the client's environment, ensuring portability, scalability, and performance. Continuous monitoring: We generate structured logs and high-quality dashboards (Power BI or QuickSight), with visual indicators that facilitate monitoring data health, alerts, and auditing. Integration with pipelines: The engines can be embedded in ingestion and transformation pipelines (Data Factory, Glue, Databricks Jobs), ensuring real-time or batch validations. Benefits: Increase data reliability Reduce rework and operational failures Strengthen regulatory compliance (LGPD, SOx) Accelerate decision-making based on quality data