“Through 2020, 35% of enterprises will implement some form of data virtualization as one enterprise production option for data integration” – Gartner
This article examines the validity of the 10 most widely held information about Data Virtualization.
What is Data Virtualization?
Data virtualization technology is based on the execution of distributed data management processing, primarily for queries, against multiple heterogeneous data sources, and federation of query results into virtual views. This is followed by the consumption of these virtual views by applications, query/reporting tools, message-oriented middleware or other data management infrastructure components. Data virtualization can be used to create virtualized and integrated views of data in-memory, rather than executing data movement and physically storing integrated views in a target data structure. It provides a layer of abstraction above the physical implementation of data, to simplify querying logic.
1. Data Virtualization tools are cheaper to maintain than traditional Data Integration tools.
Physically replicating, moving and storing data multiple times is expensive. Data Virtualization creates a virtual data layer that eliminates the need for replication or storage costs.
2. It’s a faster way to manage data.
Rather than having to wait hours or even days for your results with traditional data integration methods, data virtualization provides results in real-time.
3. It complements traditional Data Warehousing.
Did you know, data virtualization works alongside and complements traditional warehousing tools.
4. It maximizes performance.
Poor performance is often due to network latency, i.e. the delay before a transfer of data begins. data virtualization connects directly to the source and provides actionable insight in real-time.
5. It enables self-service BI (Business Intelligence).
Data Virtualization can empower business users to leverage data on their own rather than always having to rely on the technical team.
6. It ensures secure Data Governance.
Data Virtualization enables a centralized point of access to all kinds of information in the enterprise enabling security management, data governance, and performance monitoring.
7. It goes far beyond Data Federation.
Data Virtualization is a superset of the ten-year-old data federation technology. it includes the advanced capabilities of performance optimization as well as self-service search and discovery.
8. It offers a great ROI.
A typical data virtualization project pays back in less than 6 months of implementation with data virtualization, businesses can achieve 50% to 80% time saving over traditional integration methods.
9. It is more agile than traditional methods.
Data Virtualization technology includes prototyping capabilities, meaning you can test out your strategy before implementing it on an enterprise scale.
10. Data Virtualization gives the right context to Big Data fabric.
Big Data fabric enabled by data virtualization integrates data, prepares it for predictive analytics, and makes it available to the consumer in real-time.