Datactics, a leading provider of data quality software solutions, has taken a significant leap forward with the launch of its Augmented Data Quality Solution (ADQ).
This innovative solution makes faster and more efficient AI-powered data quality accessible and beneficial to all, through an enriched user interface and more expansive implementation of machine learning functions throughout.
ADQ covers the full spectrum of end-to-end data quality management. The platform provides data profiling, cleaning, matching and remediation without the need for coding, and leverages the power of AI to provide meaningful data quality insights on data breaks, causes and detecting outliers.
In today's data-driven world, enterprises face the challenge of maintaining high quality data across the organisation and ensuring that critical data is easily accessible to governance professionals. ADQ eliminates potential delays in data remediation workflows by using greater automation and no-code tooling, thereby reducing manual effort and increasing accuracy.
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ADQ seamlessly integrates with data catalogues and lineage systems such as Alation and Solidatus, accommodating both cloud-only and hybrid data architectures. This interoperability ensures that customer data management ecosystems remain harmonious and efficient.
The release of ADQ unveils a range of machine learning extensions which will allow customers of Datactics to deliver data quality improvements faster, more efficiently and with maximum business impact. Users will benefit from improved profiling, including outlier detection and automated rule suggestion. Additionally, ADQ includes a new feature called ‘Insights Hub’ which allows customers to benefit from the long histories of data quality ‘break/fix’ activities and to perform analysis into which remediations are having the most substantial business impact.
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Datactics CEO Stuart Harvey says, "ADQ makes use of the power of machine learning in a very practical way that will help a data governance professional do their job faster and better. ADQ can improve data quality time to value for an analyst struggling to choose the most efficient rules for complex data via automated rule suggestion.
Likewise, having created rules to measure and remediate broken data, ADQ can be used to further root cause analysis by understanding whether data quality improvements are making a difference over time. All of this can be done without deep technical expertise on behalf of the ADQ user. We have several international clients already using the system live, and we look forward to rolling out to new and existing customers throughout 2023 and into 2024.”
Source: Written from press release
