Gartner, Inc. just released a comprehensive comparison of the leading suppliers of Data Quality Software which included DQLabs. The Connecticut-based technology research and consulting company published this report covering data management solutions for technical professionals.
Gartner undertook this study after surveys with leading organizations revealed that capabilities provided by traditional data quality software require too much manual effort and are no longer sufficient to meet the needs of organizations operating in rapidly evolving data environments. In this highly anticipated review, several key categories were examined, and 20 criteria were rated to allow technical data and analytics professionals to assess these enterprise data quality platforms and their offerings.
For organizations that require either high degrees of data quality or are seeking a holistic approach to managing all of their data, this report would be of great use. The report categories that DQLabs rated highly are as follows:
Supporting capabilities: Describes capabilities that support core functionalities of a data quality tool, including connectivity, scalability, deployment options, and integration options
Data quality analysis and profiling: Describes capabilities that support the analysis of the structural and contextual aspects of data
Defining, assessing, and validating rules: Describes capabilities to define, create and deploy data quality rules to assess and validate the quality of a data asset
Remediation and enrichment: Describes capabilities to parse, standardize, cleanse and enrich data using a combination of automated transformation logic and manual workflows
Monitoring: Describes the capabilities to automatically track the quality of data, determine if appropriate levels are being maintained, and notify users if problems are detected
DQLabs clearly took first place by being rated by Gartner as either medium or high in 19 of the 20 listed criteria. Data management platforms like DQLabs can automate profiling, rule generation, rule deployment, monitoring, data cleansing, enrichment, and remediation workflows. Proficient data quality platforms like DQLabs are tied to data governance and use integration to metadata management solutions to deploy data quality rules, track rule deployments, share validation results, and support remediation efforts. To this extent, DQLabs was recognized as a pinnacle provider of a leading-edge augmented data management platform after careful review.
This report provides clear evidence that organizations with data management needs in the areas of data quality, defining and validating rules, remediation and enrichment as well as monitoring and supporting capabilities would be well supported by the augmented data management platform from DQLabs.
For further details regarding the results of this report please contact our DQLabs representative.