Ataccama Extends Generative AI Capabilities to Accelerate Enterprise Data Quality Initiatives

Updated data lineage, observability and data quality features in the Ataccama ONE unified data trust platform v15.4 deliver time and cost savings through automation of manual data tasks.

Ataccama, an AI-powered data management company, today announced enhancements to the Ataccama ONE unified data trust platform v15.4 that enable customers to have confidence in using their data for business-critical decision-making. In this latest release, enhancements include augmenting its AI capabilities, streamlining user experience, and simplifying task management for greater efficiency and cost reduction.

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The latest edition of Ataccama ONE includes the following new updates:

• Extended generative AI functionality: Designed for new and non-technical users, the new AI-powered features allow them to quickly build accurate DQ rules using natural language, and test and regenerate rules through new prompts. Using ONE AI, users can generate full data quality rules for completeness, saving time and aiding adoption across the organization. Additionally, descriptions for objects can now be generated for rules and terms in addition to tables.
• Unified data observability: A key component for data trust, users can run data observability manually, close issues or add newly-discovered catalog items to observed systems across all tabs.
• Quickly evaluate data lineage completeness: Users can now browse, search, filter & sort and access all objects in the lineage repository, facilitating the tracking of an attribute and seeing its sources.
• Usability improvements for task module management: The latest version speeds up workflows and allows users to customize tasks, with easier navigation, custom permissions and task listings, all providing a better user experience.

Jay Limburn, Chief Product Officer, Ataccama, said, “Data trust is the driving force behind thriving, future-proofed business. Our research found that 72% of today’s data leaders fear that not implementing AI will harm their companies’ competitiveness, and therefore, it’s no surprise that improving data quality is a top business priority. Achieving data trust empowers data teams to deliver on the promise of AI, enabling operational excellence and preparedness for external influences, to derive maximum value from data-driven insights.”

Data trust occurs when strategic technology implementation is blended with proactive, holistic data management practices across all stages of the data lifecycle:

1. Organize and secure: With Ataccama ONE, customers can use data catalog and governance capabilities to document all available assets, define who owns them and for which purposes they can be used.
2. Understand and observe: With Ataccama’s integrated data lineage, data quality, and observability tools, users get visibility into the data’s origins and reliability, consistently monitoring the asset over time to see how it has changed.
3. Improve quality: Applying data quality curation is the final step on the journey to data trust. At this point, users fix all the data quality issues with Ataccama’s market leading data quality and master data management tools to maximise the accuracy of the data and enable valuable insights, accurate reporting and informed decision-making.

For more information and full documentation release notes are available from ataccama.com or visit our Community for support.

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