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 application.
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 -
Disadvantages of Data Virtualization
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, analyze and present 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 micro services and containers. It is written in Java.
2. TIBCO data virtualization
TIBCO helps administrators and users to create a data virtualization platform for accessing the multiple data sources and data sets. It provides a builtin transformation engine to combine non-relational and un-structured 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