Published: 02 November 2022
Data quality vendors are transforming the data quality solutions market with augmented capabilities for process automation, insight discovery and next best suggestions. Data and analytics leaders must evaluate data quality vendor strengths across several critical capabilities and common use cases.
Modern data quality solutions offer augmented data quality capabilities that are driven by metadata, artificial intelligence/machine learning (AI/ML) and knowledge graphs to disrupt how we solve data quality issues. The primary differentiator among vendors is the level of automation supported by these underlying technologies across various critical capabilities and use cases.
Data quality solutions continue to transition from stand-alone applications into a set of integrated platforms to address modern data quality requirements. Data quality solutions now include features such as data catalog, data observability and data preparation and support a range of complex use cases and streamlined processes.
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