Data Virtualization In Cloud Computing

What is Data Virtualization in Cloud Computing?

Data virtualization is gathering data from multiple sources of information to create a single, logical, and virtual view of information that can be accessed by front-end solutions such as portals, applications, and dashboards without knowing the exact storage location of the data.

In other words, we can say that, In this virtualization, data is collected from multiple sources and managed in a single location without knowing more about the technical information, such as how data is collected, stored, formatted, and then arranged logically so that its virtual view can be accessed remotely by its interested people, stakeholders, and users via the various cloud services. Many large corporations, including IBM, At scale, Oracle, Cdata, and others, offer their services.

Read about: Data and Storage Virtualization, Storage Virtualization in Cloud Computing

Work of Virtualization in Cloud Computing

Virtualization in cloud computing involves abstracting physical hardware resources and creating virtual instances of servers, storage, networks, and other infrastructure components. This enables multiple virtual machines (VMs) or containers to run on a single physical machine, maximizing resource utilization and flexibility. Virtualization allows cloud providers to offer scalable, on-demand resources to users, facilitating efficient resource management and workload deployment.

Benefits of Virtualization

1. Resource Utilization: Virtualization allows for better utilization of physical hardware resources by running multiple virtual instances on a single physical server.
2. Isolation: Virtualization provides isolation between virtual instances, ensuring that failures or security breaches in one instance do not affect others.
3. Flexibility and Scalability: Virtualization enables rapid provisioning and scaling of resources, allowing organizations to adapt to changing workloads and demands.
4. Cost Savings: By consolidating multiple virtual instances onto fewer physical servers, organizations can reduce hardware and operational costs.
5. Disaster Recovery: Virtualization facilitates easy backup, migration, and recovery of virtual instances, improving disaster recovery capabilities.

Drawbacks of Virtualization

1. Overhead: Virtualization introduces overhead in terms of performance, as resources must be allocated for managing and running virtual instances.
2. Complexity: Managing virtualized environments can be complex, requiring specialized knowledge and tools for provisioning, monitoring, and troubleshooting.
3. Vendor Lock-In: Organizations may become dependent on specific virtualization technologies or providers, limiting flexibility and portability.
4. Security Concerns: Virtualized environments may introduce new security risks, such as vulnerabilities in hypervisors or misconfigurations in virtual networks.
5. Licensing Issues: Virtualization may pose challenges related to software licensing, as licensing models may not always align with virtualized environments.

Characteristics of Virtualization

1. Abstraction: Virtualization abstracts physical hardware resources, presenting them as virtual entities to users or applications.
2. Isolation: Virtualization provides isolation between virtual instances, ensuring that each instance operates independently of others.
3. Encapsulation: Virtualization encapsulates entire environments, including operating systems, applications, and data, into self-contained units.
4. Flexibility: Virtualization enables dynamic provisioning, scaling, and migration of virtual instances, allowing for agile and responsive IT environments.
5. Efficiency: Virtualization improves resource utilization and efficiency by allowing multiple virtual instances to share physical hardware resources.

Check this out: Implementation of Big data virtualization, Software Virtualization in Cloud Computing

Use of Data Virtualization in cloud computing

Virtualization is quite helpful in cloud computing. The same goes for data virtualization. Also, the following are some uses of data virtualization:

• It is used to analyze the organization's performance compared to previous years.
• It provides a mechanism for searching similar and internally related data to one another.
• It creates a secure, centralized layer for searching, discovering, and managing unified data and relationships.

The are multiple industries where data virtualization is used; let's learn about them.

Data Virtualization Tools

Data virtualization tools provide a layer of abstraction that enables users to access and manipulate data from disparate sources as if it were stored in a single location, without the need for physical data movement or replication. These tools aggregate data from various sources, such as databases, data warehouses, cloud storage, and APIs, and present it to users in a unified and consistent manner.

Key features of data virtualization tools include:

• Data Integration: Data virtualization tools integrate data from multiple sources, including structured, semi-structured, and unstructured data, into a unified view. This allows users to access and analyze data from different systems without the need for complex ETL (extract, transform, load) processes.
• Data Abstraction: Data virtualization tools abstract the underlying data sources, hiding the complexities of data storage and access from users. This simplifies data access and management, making it easier for users to work with heterogeneous data environments.
• Data Federation: Data virtualization tools support data federation, allowing users to query and manipulate data from multiple sources using a single interface. This enables seamless integration of data from disparate systems, applications, and databases.
• Real-Time Data Access: Many data virtualization tools offer real-time data access capabilities, allowing users to access and analyze data as it is updated or modified in source systems. This ensures that users have access to the most up-to-date information for decision-making and analysis.
• Data Governance: Data virtualization tools provide features for data governance, including data security, access control, and metadata management. This ensures that data is accessed and used in compliance with organizational policies and regulatory requirements.

Industries using Data Virtualization

The following are the list of industries where data virtualization is used:

• Finance 
• Government
• Communication and Technology
• Healthcare 
• Manufacturing

Now let’s learn some advantages and disadvantages of data virtualization.

Advantages of Data Virtualization in cloud computing

The following are the advantages of data virtualization:

• It provides a variety of security features that allow users to securely store their personal and professional information.
• It has an easy-to-use interface for creating customized views and provides a variety of resources for quick and easy deployment.
• It enables users to access data without having to worry about where it is stored on the memory.
• It lowers costs by eliminating data replication and improves business user efficiency by delivering data in real-time.

Disadvantages of Data Virtualization in cloud computing

Data virtualization has the following disadvantages:

• It has a high implementation cost and causes issues with availability and scalability.
• Availability issues are there because third-party providers maintain availability.
• Although it saves time during the virtualization implementation phase, it takes more time to generate the desired result.

This concludes our topic of data virtualization. Now, let's move on to FAQs.

Frequently Asked Questions

What is data storage virtualization in cloud computing?

Data storage virtualization in cloud computing refers to the abstraction of physical storage resources, such as disk drives, storage arrays, and cloud storage services, into a virtualized layer. 

What is the principle of data virtualization?

The principle of data virtualization is based on the abstraction and integration of data from multiple sources into a unified and consistent view, without physically moving or replicating the data.

What are some industries where data virtualization is used?

The industries where data virtualization is used are Finance, Government, Communication and Technology, Healthcare, and Manufacturing.

What is application virtualization?

This type of virtualization enables a user to have remote access to an application hosted on a server. The application's personal information and other characteristics are saved on the server, yet it can still be run on a local workstation through the internet. For example, consider a user who has to run two separate versions of the same software.

Conclusion

This article extensively discussed Data virtualization in cloud computing. We learned about data virtualization in detail. We also learned the uses, advantages, and disadvantages of data virtualization.

Refer here to know more about cloud computing in detail.

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