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Data Science

High-Quality Data is Not Easy to Find

Artificial intelligence/machine learning (AI/ML) brings about the convergence of analytics, data science, and automation to accelerate successful digital transformations and fuel positive business outcomes. Building AI/ML applications is an iterative process that can be broken down into four key stages: Data sourcing, data preparation, model testing and deployment, and model evaluation.

Cloud computing platforms make it possible to train and test dozens of different models simultaneously to determine the ideal model. However, the availability of suitable data is still one of the most significant challenges that organizations and data scientists face.

The Denodo Platform is a logical data management solution that provides a centralized data access layer enabling anyone to find, access, integrate, and share data securely, in real time, regardless of where the data may reside.

The AI community is facing a bifurcation of “model-centric” and “data-centric” AI, because data quality and consistency improve AI accuracy more efficiently than tweaking models.”

Gartner - Top Trends in Data and Analytics, 2022 - 11 March 2022

Self-service Analytics

The Denodo Platform

A logical data management, data integration, and data delivery solution that provides real-time access to curated, high-quality data. Powered by data virtualization, the Denodo Platform establishes a logical abstraction layer across all enterprise data assets that enables immediate access to any dataset without needing to first copy or replicate it. When a user connects to data and requests it, the Denodo Platform retrieves that data from one or more backend systems in real time, integrates it into business-friendly views, and delivers it to the user. For data scientists, self-service data discovery and access address data-sourcing challenges, while robust data transformation capabilities address data preparation challenges. Rather than spending most of their time on data sourcing and preparation, data scientists can focus on continually improving their models.

Architecture Data Virtualization

Self-service Analytics


Data Access

The centralized logical data access layer enables anyone to quickly and easily access data, regardless of where it resides.

Data Discovery

TThe data catalog enables users to browse, discover, and use data assets located anywhere in the enterprise. With the AI-powered recommendations engine, tools to aid collaboration, and smart-search features, users know they can trust the data they discover.


With the broadest data delivery options, including JDBC, ODBC, ADO.NET, SOAP or RESTful web services, OData, GraphQL, GeoJSON, exports to Microsoft Excel/SQL, Tableau Data Extracts, and JMS message queues, users can access data in their preferred ways.

In Forrester’s recent Total Economic Impact™ (TEI) of Data Virtualization Using the Denodo Platform, Forrester found that data preparation times for data scientists were reduced by 67%. Forrester’s TEI methodology helps companies demonstrate, justify, and realize the tangible value of IT initiatives to both senior management and other key business stakeholders.

Read the full Forrester Study

The Total Economic Impact of Data Virtualization using the Denodo Platform.

Forrester TEI
Data Science

Customer Success Stories

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