Data virtualization is the process of retrieve data from various resources without knowing its type and physical location where it is stored. It collects heterogeneous data from different resources and allows data users across the organization to access this data according to their work requirements. This heterogeneous data can be accessed using any application such as web portals, web services, E-commerce, Software as a Service (SaaS), and mobile applications.
We can use Data Virtualization in the field of data integration, business intelligence, and cloud computing.
Advantages of Data Virtualization
There are the following advantages of data virtualization –
- It allows users to access the data without worrying about where it resides on the memory.
- It offers better customer satisfaction, retention, and revenue growth.
- It provides various security mechanism that allows users to safely store their personal and professional information.
- It reduces costs by removing data replication.
- It provides a user-friendly interface to develop customized views.
- It provides various simple and fast deployment resources.
- It increases business user efficiency by providing data in real-time.
- It is used to perform tasks such as data integration, business integration, Service-Oriented Architecture (SOA) data services, and enterprise search.
Disadvantages of Data Virtualization
- It creates availability issues, because availability is maintained by third-party providers.
- It required a high implementation cost.
- It creates the availability and scalability issues.
- Although it saves time during the implementation phase of virtualization but it consumes more time to generate the appropriate result.
Uses of Data Virtualization
There are the following uses of Data Virtualization –
1. Analyze performance
Data virtualization is used to analyze the performance of the organization compared to previous years.
2. Search and discover interrelated data
Data Virtualization (DV) provides a mechanism to easily search the data which is similar and internally related to each other.
3. Agile Business Intelligence
It is one of the most common uses of Data Virtualization. It is used in agile reporting, real-time dashboards that require timely aggregation, analysis, and presentation of the relevant data from multiple resources. Both individuals and managers use this to monitor performance, which helps to make daily operational decision processes such as sales, support, finance, logistics, legal, and compliance.
4. Data Management
Data virtualization provides a secure centralized layer to search, discover, and govern the unified data and its relationships.
Data Virtualization Tools
There are the following Data Virtualization tools –
1. Red Hat JBoss data virtualization
Red Hat virtualization is the best choice for developers and those who are using microservices and containers. It is written in Java.
2. TIBCO data virtualization
TIBCO helps administrators and users to create a data virtualization platform for accessing multiple data sources and data sets. It provides a built-in transformation engine to combine non-relational and unstructured data sources.
3. Oracle data service integrator
It is a very popular and powerful data integrator tool which is mainly worked with Oracle products. It allows organizations to quickly develop and manage data services to access a single view of data.
4. SAS Federation Server
SAS Federation Server provides various technologies such as scalable, multi-user, and standards-based data access to access data from multiple data services. It mainly focuses on securing data.
Denodo is one of the best data virtualization tools which allows organizations to minimize the network traffic load and improve response time for large data sets. It is suitable for both small as well as large organizations.
Industries that use Data Virtualization
- Communication & Technology
In Communication & Technology industry, data virtualization is used to increase revenue per customer, create a real-time ODS for marketing, manage customers, improve customer insights, and optimize customer care, etc.
In the field of finance, DV is used to improve trade reconciliation, empowering data democracy, addressing data complexity, and managing fixed-risk income.
In the government sector, DV is used for protecting the environment.
Data virtualization plays a very important role in the field of healthcare. In healthcare, DV helps to improve patient care, drive new product innovation, accelerating M&A synergies, and provide a more efficient claims analysis.
In manufacturing industry, data virtualization is used to optimize a global supply chain, optimize factories, and improve IT assets utilization.