Ataccama ONE v16.2 uses AI to simplify data lineage for business
The company stated that the new version addresses long-standing challenges in enterprise data governance, particularly the trust gap between business teams and IT departments. By providing compact, plain-language lineage views and secure on-premises metadata extraction, Ataccama targets the need for transparency in complex data environments. Expanded pushdown profiling capabilities are also included to provide more comprehensive data quality insights.
One key issue identified by Ataccama is the limited ability for business users to visualise data origins and transformations without specialist support. The reliance on IT to explain data logic is seen as a barrier to efficient decision-making and increases risk. Recent research from Forrester highlights that only 20% of business decision-makers are currently self-sufficient with analytics tools, suggesting widespread challenges with data access and understanding across industries.
The new features aim to close this trust gap by converting complex data workflows into accessible, plain-language descriptions. Business users will be able to track a data point's origin and understand profiling or quality checks independently of technical teams. In real-world settings such as financial services, a data steward can see how a risk score is calculated or how a transaction passes through quality controls, facilitating shorter audits and faster decision-making. "We're seeing enterprise data projects increasingly kick off in the business, not just in IT, and that changes everything," said Jessica Smith, VP of Data Quality at Ataccama. "The teams driving these initiatives need to understand where the data comes from, how it's changed, and whether it can be trusted. That's why we've focused on making complex data processes, like profiling, quality checks, and lineage, clear and usable to everyone. Because if data is going to scale across the business, it has to work for the people who are using it."
The company describes several core updates in the v16.2 release. The AI-powered data lineage feature automatically generates readable descriptions showing how data is transformed both upstream and downstream, including filters, joins, and calculations. This makes it possible for business users to see the logic behind datasets without needing to interpret SQL queries.
The compact lineage diagrams provide simplified, high-level views of data flows, with the option to explore detailed steps as needed. This feature is designed to help teams identify issues, respond to audit requests, and align stakeholders on data processing practices across the organisation.
Edge processing for secure lineage is another new capability, enabling companies to extract metadata from on-premises or restricted environments without transferring sensitive data to the cloud. Ataccama states that this functionality helps organisations to maintain compliance, reduce risk, and maintain full visibility into their data pipelines, regardless of their infrastructure.
The update also expands pushdown support and performance for data profiling and quality workloads. Users can now run these tasks in pushdown mode for platforms such as BigQuery and Azure Synapse, minimising data movement and enhancing performance for larger workloads. In addition, volume support for Databricks Unity Catalogue has been introduced to further optimise execution on modern cloud platforms.
According to Ataccama, the new version of its data trust platform is intended to strengthen daily data governance while underpinning more scalable and compliant AI and analytics initiatives. The company positions its integrated approach as key to enabling businesses to unlock the value of their data for operational, analytical, and AI-driven purposes.
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