Actian with its Winter 2025 Data Intelligence Platform release added self-serve data access requests, data products with a marketplace and user experiences for data consumers and producers.
The Actian Data Intelligence Platform was previously known as the Zeenea Data Discovery Platform. Actian, the data division of HCLSoftware, acquired Zeenea last year. The platform includes a centralized data catalog, active metadata management, data quality and lineage, governance and an enterprise data marketplace.
Marketplaces for software and data products is one of the key trends to watch for enterprise software. Data products are also critical given enterprises want easy access so they can enhance artificial intelligence projects.
- Enterprise software 2025: Three big shifts to watch
- AWS Marketplace adds 'Buy with AWS' as it expands reach, woos procurement departments
- Big software deals closing on AWS Marketplace, rival efforts
- Building Vibrant Marketplace Ecosystems for the Future
Actian CTO Emma McGrattan data quality, access and governance is critical to AI projects. "Data quality and governance are components to something that's bigger--data intelligence," said McGrattan. "Data intelligence is really understanding your data so it will be able to do something."
According to Actian, the Winter 2025 release of its Data Intelligence Platform sets the stage to democratize data access with control and compliance.
Additions to the Actian Data Intelligence Platform include:
- Self-serve data access to a data catalog. Actian is automating how users request and access data with governance, controls and audit trails.
- Synchronization with data quality solutions and data lineage visualization.
- An integrated enterprise data marketplace (Zeenia Enterprise Data Marketplace) with an e-commerce experience. The Actian enterprise data marketplace builds on the Actian Federated Data Catalog's metadata foundation.
Chirag Mehta, an analyst at Constellation Research, said access to high-quality data with governance is one of the biggest challenges for AI projects. "With the rise of AI and companies wanting to accelerate their timelines, having data in the right place with the right quality and access is the biggest problem," said Mehta. "What's slowing down AI projects is not so much the technology, infrastructure or data structure as much as it having data in the right place."