Empowering business teams with Ataccama ONE v16.2: Bridging the data trust gap

Ataccama, a leading data trust company, has unveiled Ataccama ONE v16.2, the recent upgrade to its unified data trust platform. This release promises an intuitive interface for business users to understand the journey of data across systems without any SQL knowledge.

Navigating data sources and transformations presents a challenge for most business teams, who often depend on technical staff to decode data logic. This dependency curtails decision-making and exposes organizations to unnecessary risks. According to Forrester, a mere 20% of business decision-makers can self-serve with analytics tools. The trust gap hampers effective data governance, analytics scaling, and adapting to business speeds.

Ataccama addresses this gap by translating intricate data logic into understandable language. Business users can now easily trace a data point's origins and scrutinize how it undergoes profiling and filtering, eliminating the reliance on IT departments. Ataccama elucidates data flows alongside plain-language descriptions of steps behind every figure.

In financial services, for instance, a data steward can swiftly verify the origin of a risk score or the path of a flagged transaction through quality checks and enhancements. This transparency expedites reviews, simplifies audits, and equips business teams with the confidence to act decisively.

“We’re seeing enterprise data projects increasingly kick off in the business ... 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," said Jessica Smith, VP of Data Quality at Ataccama. “

Ataccama ONE v16.2 has some key capabilities that bolster day-to-day governance and lay the foundation for more robust, compliant AI projects, ensuring data can be efficiently scaled across the business landscape while serving the needs of its users. These include

• AI-powered data lineage: Automates the generation of user-friendly descriptions of data transformations. It clarifies filters, joins, and calculations, enabling users to understand dataset logic without reading SQL.
• Compact lineage diagrams: Simplifies and presents high-level data flows, facilitating issue identification, audit query resolutions, and stakeholder alignment on data paths.
• Edge processing for secure lineage: Allows metadata extraction from restricted environments while avoiding sensitive data transfer to the cloud, thus upholding compliance and minimizing risks.
• Expanded pushdown support: Enhances pushdown execution for BigQuery and Azure Synapse, reducing data movement and optimizing performance for sizable workloads.