Datameer introduced on Wednesday Neebo, its product that enables analytics and data science teams to find, combine, and publish trusted information assets in hybrid landscapes.
Neebo's self-service platform enables analytics professionals and data scientists to initiate projects in minutes and promptly answer analytics questions or build new models, thereby enabling greater business agility. Neebo provides a unified access point for analysts, data scientists, and business stakeholders to more effectively leverage all their data science and analytics assets across the enterprise.
Neebo works with information assets of any type such as data, documents, reports, code, dashboards, SaaS applications, and data science models, no matter where they reside: on-premises, in the cloud, in SaaS applications, or in web services.
Neebo uses virtualization and AI techniques to support a number of key capabilities. With Neebo, teams can connect to analytics and data science assets and use them no matter where they reside; find and explore these assets to help answer analytics questions; combine assets to create new ones that are customized to solve the problem at hand; publish assets that can be consumed by business intelligence and data science tools, and share and collaborate to re-use assets and build trust and knowledge across the enterprise.
By providing virtualized access to analytics assets, Neebo eliminates costly and error-prone movement, keeps assets securely in place, and ensures trusted, single source of truth for each asset. Neebo also includes security and governance capabilities that complement and integrate into existing frameworks.
Neebo embeds AI in many of its features including: assisting with discovery of assets so teams can find the optimal ones for their specific problems, providing data blend suggestions, and optimizing queries and caching. All this makes the work of analysts and data scientists easier and faster.
Neebo manages a wide variety of assets covering both traditional analytics and data science. This helps organizations unify all their analytics efforts and integrates data science initiatives into mainstream analytics processes and governance.
In September, Datameer announced general availability of Datameer X, a new release of its data preparation and exploration software built for data scientists and machine learning engineers. Now, organizations can speed up machine learning analytics cycles and create robust data flows that feed more data into machine learning models to increase their accuracy.
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