Provectus, a Silicon Valley artificial intelligence (AI) consultancy, announced the release of Open Data Discovery (ODD) Platform, a free open-source data discovery and observability tool for data-driven organizations looking to democratize their data by making it more discoverable, manageable, observable, reliable, and secure.
ODD Platform is a next-generation solution for data observability and reliability. It enables enterprises to streamline all data handling processes, to facilitate collaboration between data scientists and data engineers, reduce data discovery time, and minimize data downtime. It offers engineers an easy-to-use environment where they can manage data by using a variety of built-in tools, to make their data entities more reliable, observable, and easily discoverable. The ODD Platform offers IT organizations a robust solution for the understanding and management of their data.
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“Historically, data catalogs have helped data-first organizations to keep data organized. You could adopt an open-source data catalog or purchase a SaaS solution to make your data discoverable right away,” says German Osin, Senior Solutions Architect at Provectus. “But data catalogs do not evolve fast enough to accommodate modern requirements for better integrated, faster, and more transparent data tools. They do not solve such challenges as lack of standardized data collection, incompatibility of different catalogs, limited data lineage, inefficient data quality and observability practices, and other specifics of ML development.”
ODD Platform is designed to help organizations close the gaps that data catalogs cannot cover. For that purpose, it is built based on five principles:
- Utilization of an open metadata standard
- Using a federation strategy to allow for building of meta catalogs
- Inclusion in the ML ecosystem as first-class citizens
- Enablement of company-wide data discovery and observability
- Full-scale integration with other open standards
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These principles are realized through such features as:
- Universal open standards for metadata collection
- Democratization of data across any organization (data self-service)
- Integration with other open standards, data catalogs, tools, and ML ecosystems
- Support of various data sources (BI, ML, ETL, ELT, data quality tools, warehouses, etc.)
- Building of meta catalogs by federating any data catalogs in use
- Quick and easy deployment without the required provision of a complex infrastructure
- End-to-end data lineage across all tools used in the company
- Alerts for changes and issues, to issue notifications and alerts if any data entities have been affected
- Robust data enrichment with data quality tests
- No access to actual data for security reasons (operates with metadata only)
“We are excited to release ODD Platform and offer the engineering community a powerful tool to democratize data at scale,” says Stepan Pushkarev, CTO of Provectus. “We hope OOD platform will be a viable alternative to siloed data catalogs, and that it will enable data science and data engineering teams to accelerate and facilitate data discovery, minimize data downtimes, and, most importantly, focus on building data products. Inefficient metadata exchanges between data tools is so mundane, it has become accepted as unavoidable, and we plan to change that.”
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