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Enhance your Data Strategy with Agility

Invigorate Data Strategy

Integrating data virtualization alongside a data warehousing solution can offer several benefits to your organization. Data virtualization complements data warehousing by providing real-time data access, agility, and simplified integration across various sources. It  improves an organization's ability to make data-driven decisions, reduce data movement complexity, and enhance overall efficiency in managing and accessing data.

Gain valuable real-time insights, simplify the integration of data, and empower yourself with self-service analytics using data virtualization.


Several business needs  might compel  your organization to implement data virtualization within a data management strategy. These needs are often centered around common data challenges impeding the achievement of strategic business objectives. . Here are a few prevalent reasons why companies may choose to adopt data virtualization as part of their data management strategy.

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    As organizations accumulate data from various sources, data integration becomes complex and time-consuming. Data virtualization simplifies this process by providing a unified view of data across disparate sources, reducing the need for extensive ETL processes.
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    Companies often deal with data stored in different formats, databases, and systems, both on-premises and in the cloud. Data virtualization provides a way to access and integrate data from these heterogeneous sources seamlessly.
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    In today's fast-paced business environment, companies need timely insights to make informed decisions. Data virtualization enables real-time or near-real-time access to data, allowing organizations to respond quickly to changing market conditions and customer demands.
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    As companies move to cloud-based infrastructures, integrating data from on-premises and cloud sources becomes essential. Data virtualization can facilitate this transition by providing a unified data access layer across different environments.
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    Data virtualization platforms offer features for enforcing security controls, access permissions, a auditing and tagging sensitive data. This helps ensure compliance with data governance regulations and protects sensitive information.
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    Data duplication across systems can lead to data integrity and security issues and increased storage costs. Data virtualization enables users to access and analyze data without creating redundant copies, ensuring data consistency.

Tools and Assets

A successful data virtualization implementation requires thoughtful planning, a well-rounded toolset, and dedicated resources with subject matter expertise to achieve the desired benefits of real-time data access, simplified integration, and improved analytics capabilities.

Axxiome has a strategic partnership with market leading data virtualization provider Denodo a Gartner® Magic Quadrant™ leader for Data Integration Tools, for 3 years in a row. Axxiome is a value-added reseller of Denodo and brings unique expertise and experience developing data virtualization solutions within the financial services sector.
The primary objective of implementing data virtualization is to enhance the flexibility of providing data management solutions by concentrating on the principles of simplifying complexity, eliminating data duplication, and enhancing the timeliness of accessible data for decision making. 
Industry Focus
We are a leading provider of technical services to the financial services industry. Axxiome has been providing core banking, digital banking and data management solutions across the globe for more than 15 years.

Axxiome's data team is well versed in a broad range of data advisory consulting and has proven capabilities implementing data virtualization solutions.


  • Modernize data infrastructure by replacing legacy systems with modern cloud applications
  • Protect data by insulating source systems and preventing unintentional changes
  • Reduce expense with zero data replication and decreased storage cost
  • Increase business user productivity with real-time data
  • Enable self-service capability reducing development resources by 25%
  • Enforce centralized data governance and security


What is data virtualization? Data virtualization is an approach that allows organizations to access and integrate data from various sources without the need to physically move or replicate the data. It provides a unified, virtualized view of data that can be queried and analyzed in real-time, improving agility and data utilization.
How does data virtualization differ from traditional ETL processes? Unlike traditional Extract, Transform, Load (ETL) processes that involve moving and transforming data into a central repository, data virtualization enables data access directly from source systems. ETL requires data duplication, whereas data virtualization offers real-time access without creating redundant copies.
What types of data sources can be integrated using data virtualization? Data virtualization can integrate a wide range of data sources, including databases, data warehouses, APIs, cloud services, spreadsheets, flat files, and more. It accommodates both structured and unstructured data from diverse platforms.
Is data virtualization secure? Yes, data virtualization platforms such as Denodo offer robust security features. Access controls, encryption, authentication, and audit trails can be implemented to ensure data privacy and compliance with regulations like GDPR or HIPAA. Security measures are enforced across the unified data view.
Can data virtualization handle large datasets? Yes, data virtualization can handle large datasets. Performance optimization techniques such as caching and query optimization help ensure that data retrieval remains efficient, even when dealing with significant volumes of data.
How does data virtualization support analytics and reporting? Data virtualization enhances analytics by providing a single point of access to data from multiple sources. This unified view enables users to perform cross-source analyses, create comprehensive reports, and gain deeper insights without the need to manually integrate data.