Data Virtualization Statistics


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Steve Goldstein
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Data Virtualization Statistics 2023: Facts about Data Virtualization outlines the context of what’s happening in the tech world.

LLCBuddy editorial team did hours of research, collected all important statistics on Data Virtualization, and shared those on this page. Our editorial team proofread these to make the data as accurate as possible. We believe you don’t need to check any other resources on the web for the same. You should get everything here only 🙂

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Top Data Virtualization Statistics 2023

☰ Use “CTRL+F” to quickly find statistics. There are total 15 Data Virtualization Statistics on this page 🙂

Data Virtualization “Latest” Statistics

  • According to Denodo data, there are only 1,999,984 distinct clients in that view; as a result, only 0.69% of the total is moved as a result of this optimization, which is a significant gain in speed.[1]
  • Single-column uses 100% of the data presented in the dataset to construct statistics.[1]
  • While implementing new data services, a top semiconductor company saved 90% of its resources.[2]
  • A telecom corporation cut the burden of IT operations employees by 40%, saving more than $250,000 annually.[2]
  • Amgen, a major U.S. biopharmaceutical business, increased per-plant revenue by $10-$30 million while improving medication production yield by 1%-3%.[2]
  • Building and maintaining data integration procedures for tying together dispersed data assets would cost 45% less for businesses using data virtualization as a delivery strategy by 2020.[2]
  • Data virtualization reduces data integration resources by 30%.[2]
  • One of Spain’s leading telecom companies, Jazztel, doubled customer retention while increasing first-call resolution rates to 95%.[2]
  • The use of data virtualization can reduce the operational costs of a business by up to 30%.[2]
  • Data virtualization can save 50% of the time of a business by up to 50%.[2]
  • Customers of Denodo from major organizations and mid-market businesses across 30 sectors have realized more than 400% returns and millions of dollars in benefits in less than six months.[3]
  • Data virtualization can increase the productivity of a business by up to 300%.[3]
  • In 2022, 60% of all institutions will enforce data virtualization as their key delivery style in data integration architecture.[3]
  • The usage of data virtualization can reduce the use of development resources of a business by 80%.[3]
  • Data virtualization has 30% swifter access to data than ETL processes.[3]

Also Read

How Useful is Data Virtualization

At its core, data virtualization aims to provide a single, unified view of all the data scattered across disparate sources within an organization. By creating a virtual layer that abstracts the underlying data sources, data virtualization allows analysts and decision-makers to access and query data without having to worry about where it is physically stored. This can significantly reduce the time and effort required to access and analyze data, leading to faster insights and more informed decision-making.

One of the key benefits of data virtualization is its ability to integrate data in real-time, enabling users to access the most up-to-date information available. This is particularly valuable in today’s fast-paced business environment, where making decisions based on outdated or incomplete data can lead to costly mistakes. By providing a real-time view of data from multiple sources, data virtualization enables organizations to respond quickly to changing market conditions and make better-informed decisions.

Data virtualization also offers a more flexible approach to data integration compared to traditional methods such as ETL (extract, transform, load) processes. With ETL, data must be copied from source systems to a central data warehouse before it can be analyzed, which can be time-consuming and resource-intensive. In contrast, data virtualization allows users to access data in its original location, eliminating the need for data duplication and reducing the complexity of data integration processes.

Furthermore, data virtualization can help organizations reduce their data management costs by eliminating the need for costly hardware investments and maintenance. By providing a virtual view of data across disparate sources, data virtualization can help organizations make more efficient use of their existing resources and streamline their data management processes. This can lead to significant cost savings over time and help organizations allocate their resources more effectively.

Another benefit of data virtualization is its ability to improve data governance and security. With data scattered across multiple sources, organizations often struggle to maintain control over their data and ensure compliance with data privacy regulations. Data virtualization can help address these challenges by providing a centralized view of all the data within an organization and enabling organizations to implement consistent data governance policies and security measures.

Despite these benefits, however, data virtualization is not a one-size-fits-all solution. Organizations must carefully assess their specific needs and requirements before implementing data virtualization to ensure that it aligns with their business goals and objectives. Additionally, data virtualization is not a silver bullet solution that can solve all data management challenges on its own. It requires careful planning, implementation, and ongoing maintenance to ensure its effectiveness and sustainability.

In conclusion, data virtualization offers significant benefits in terms of data integration, real-time access to data, flexibility, cost savings, and improved governance and security. However, its usefulness ultimately depends on how well it is implemented and integrated into an organization’s existing data management processes. With careful planning and consideration, data virtualization can be a valuable tool for organizations looking to improve their data management capabilities and gain a competitive edge in today’s data-driven business environment.

Reference


  1. denodo – https://community.denodo.com/kb/view/document/Denodo%20Query%20Optimizations%20for%20the%20Logical%20Data%20Warehouse
  2. denodo – https://www.denodo.com/en/data-virtualization/benefits
  3. denodo – https://www.denodo.com/en/data-virtualization/overview

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