Data Virtuality was developed as a solution to address the growing need for efficient data integration and management across diverse systems. It was created to enable organizations to access and analyze data in real-time without the necessity of physical data replication. The technology emerged as a response to the challenges posed by the increasing volume and variety of data sources, aiming to provide a seamless and unified view for better decision-making processes.
Data Virtuality
Data Virtuality is a data integration technology that enables real-time data access and management by creating a virtual layer over disparate data sources. It allows users to query, combine, and analyze data from multiple systems without the need for physical data movement or replication, providing a unified view of the organization's data landscape.
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Database Technologies
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About Data Virtuality
Strengths of Data Virtuality include real-time data integration, flexibility in connecting diverse data sources, and reduced need for data replication. Weaknesses might involve complexity in setup for non-technical users and potential performance issues with very large datasets. Competitors include Denodo, Tibco Data Virtualization, and IBM Cloud Pak for Data.
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How to hire a Data Virtuality expert
A Data Virtuality expert must have strong SQL proficiency for querying and data manipulation, experience with data integration and ETL processes, and familiarity with various databases and data sources. Knowledge of data modeling and virtualization concepts is essential, along with the ability to troubleshoot performance issues. Understanding of API integrations and experience with BI tools can also be beneficial.
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