About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Datactics Brings AI-Powered Augmented Data Quality Solution to Market

Subscribe to our newsletter

Datactics, a provider of data quality software solutions, has productised the Augmented Data Quality Solution (ADQ) it previewed in June 2023 and is working with customers on an upgrade rollout. The solution is designed to make 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.

ADQ covers the spectrum of end-to-end data quality management including data profiling, cleaning, matching and remediation without the need for coding, and uses the power of AI to provide meaningful data quality insights on data breaks, causes and outliers. By reducing manual effort and increasing accuracy the solution also eliminates potential delays in data remediation workflows.

“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,” says Stuart Harvey, CEO at Datactics. “It can improve data quality time to value for an analyst struggling to choose the most efficient rules for complex data via automated rule suggestion. 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.”

ADQ includes machine learning extensions that will allow Datactics’ customers 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. A new feature, Insights Hub, allows customers to benefit from histories of data quality ‘break/fix’ activities and to perform analysis into which remediations are having the most substantial business impact. It also integrates with data catalogues and lineage systems such as Alation and Solidatus, accommodating both cloud-only and hybrid data architectures.

Harvey says several international clients are already using the system live, and it will be rolled out to other new and existing customers throughout 2023 and into 2024.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: End-to-End Lineage for Financial Services: The Missing Link for Both Compliance and AI Readiness

The importance of complete robust end-to-end data lineage in financial services and capital markets cannot be overstated. Without the ability to trace and verify data across its lifecycle, many critical workflows – from trade reconciliation to risk management – cannot be executed effectively. At the top of the list is regulatory compliance. Regulators demand a...

BLOG

Financial Institutions ‘Layering’ New Risks as Report Highlights Greenwashing Exposure

The number of financial institutions flagged for greenwashing climbed substantially in the past year, highlighting both the vulnerability of individual firms and the need to integrate greenwashing risk management into decision-making processes.. The sector remained the worst offender for overstating their progress or making vague or misleading claims, the report by sustainability risk data company...

EVENT

Data Management Summit New York City

Now in its 15th year the Data Management Summit NYC brings together the North American data management community to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

GUIDE

Regulatory Data Handbook 2025 – Thirteenth Edition

Welcome to the thirteenth edition of A-Team Group’s Regulatory Data Handbook, a unique and practical guide to capital markets regulation, regulatory change, and the data and data management requirements of compliance across Europe, the UK, US and Asia-Pacific. This year’s edition lands at a moment of accelerating regulatory divergence and intensifying data focused supervision. Inside,...