Data virtualization
- Data virtualization is an approach to data management that permits an application to retrieve and manipulate data without requiring technical details about the data, like how it's formatted at source, or where it's physically located, and may provide one customer view of the general data.
- Most recent implementation of the data virtualization concept is cloud computing technology. Data virtualization software is usually used in tasks such as: Data integration, Business Intelligence.
Data Virtualization
Advantages of Data Virtualization:
- Provides a user-friendly interface to develop customized views.
- Reduces costs by removing data replication.
- Increases business user efficiency by providing data in real-time.
- Provides various simple and fast deployment resources.
Disadvantages of Data virtualization:
- Creates an availability issue.
- Creates a scalability issue.
- High cost of implementation.
- Requires several links in a chain that must work together cohesively.
- Creates a security risk.
Uses of Data Virtualization
Uses of Data Virtualization
Analyze performance
- Data virtualization is used to analyze the performance of the organization compared to previous years.
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.
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.
Data Management
- Data virtualization provides a secure centralized layer to search, discover, and govern the unified data and its relationships.
Data Virtualization Tools
Tools of Data Virtualization
Red Hat JBoss data virtualization
TIBCO data virtualization
- TIBCO helps administrators and users to make a data virtualization platform for accessing the multiple data sources and data sets. It provides a built-in transformation engine to mix non-relational and un-structured data sources.
Oracle data service integrator
- It is a really popular and powerful data integrator tool which is especially worked with Oracle products. It allows organizations to quickly develop and manage data services to access single view of data.
SAS Federation Server
- SAS Federation Server provides various technologies like scalable, multi-user, and standards-based data access to access data from multiple data services. It mainly focuses on securing data.
Denodo
- Denodo is one among the simplest data virtualization tools which allows organizations to attenuate the network traffic load and improve reaction time for giant data sets. It's suitable for both small also as large organizations.
Industries that use Data Virtualization
Industries of Data Virtualization
Communication & Technology
- In this technology, 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.
Finance
- Data Virtualization is used to enhance trade reconciliation, empowering data democracy, addressing data complexity, and managing fixed-risk income.
Government
- In the field of Government, DV is used for protecting the environment.
Healthcare
- In healthcare, DV helps to enhance patient care, drive new product innovation, accelerating M&A synergies, and supply a more efficient claims analysis.
Manufacturing
- Data virtualization is employed to optimize a worldwide supply chain, optimize factories, and improve IT assets utilization.
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