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Scratching the Surface of Data Virtualization

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Scratching the Surface of Data Virtualization

In this article, we discuss the advantages of data virtualization, use cases for implementing it, and tools available for teams to use.

· Big Data Zone ·
Free Resource

What Is Data Virtualization?

Data Virtualization is an advanced approach to data integration. It is an easier way to integrate, federate, and transform data from multiple data sources into a single, unified environment in real-time. With Data Virtualization, you’re not just collecting different data sources (such as ETL, ESB, and other middleware) but connecting them and leveraging existing Data Warehouse, Big Data lakes, or different data infrastructures already in place.

Therefore, Data Virtualization has the ability to provide a holistic view of business operations and quickly help identify new value possibilities.  Please note, the data can easily be accessed or shared by other applications, without replicating the data through the “virtual” metadata layer.


You may also like: Data Virtualization — The Evolution of the Data Lake.


When Does an Organization Need a Data Virtualization Solution?

1. Data prep time is delaying a business’ ability to make decisions and take advantage of opportunities: Data Virtualization is ideal for this situation where data demands change quickly and where access to the data in real-time could be critical to business outcomes.

2. When your data's dispersed, and some of it resides outside your firewall or the cloud: Data Virtualization provides access to all of your data sources, allowing you to federate and align all of those sources into a single, consumable data model.

3. Are infrastructure and maintenance costs for data warehousing and storage too high: Because Data Virtualization solution does not create duplications of data, you will eliminate most of the costs associated with traditional data management.

Benefits of Data Virtualization

1. It is cheaper to maintain than traditional integration tools.

2. It is a faster way to manage data.

3. It complements traditional data warehousing.

4. It maximizes performance.

5. It enables self-service BI.

6. It ensures secure data governance.

7. It goes far beyond data federation.

8. It gives the right context to Big Data Fabrics.

Data Virtualization Tools

Here is a list of Top data Virtualization Software!

Denodo

Denodo is one of the best choices for organizations of any size looking to not just virtualize their data, but to also understand what data they have. The data catalog feature that has landed in the latest version of Denodo is a powerful feature for data virtualization users, offering the ability to not just combine and virtualize data but to identify and catalog data.

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Red Hat JBoss Data Virtualization

Red Hat Data Virtualization is a good choice for developer-led organizations and those that are using microservices and containers to build and enable a virtual data layer that abstracts disparate data sources.

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TIBCO Data Virtualization

TIBCO acquired this Data Virtualization application technology from Cisco in 2017 and has steadily improved it in the years since then. The ability to easily enable data to be used in other applications is a key capability.

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IBM Cloud Pak for Data

For organizations looking for a converged solution that handles data collection and analysis, IBM Cloud Pak for Data is a good choice. The offering was formerly known as IBM Cloud Private for Data and was rebranded in 2018.

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Informatica-PowerCenter

For organizations looking for a leading data virtualization tool with integrated data quality tools, PowerCenter is a solid choice. PowerCenter is consistently rated as a top data integration tool from analyst firms for its powerful set of features.

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Data Virtuality Logical Data Warehouse

Data Virtuality is a great fit for organizations with large data sets that perhaps cannot be easily virtualized with other solutions. Instead of just providing access through a virtual layer, the system can also replicate large data sets for faster query performance.

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Atscale Virtual Data Warehouse

Atscale's' Virtual Data Warehouse is a good choice for organizations that already have established data analytics processes and are looking to connect existing Business Intelligence tools to disparate sources of data, without the need to actually copy the data.

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Actifio Virtual Data Pipeline (VDP)

For organizations that need the reliability of an on-premises data virtualization solution, Actifio is a great choice. The company also offers a virtual cloud version, which is a fit for certain use cases.

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Conclusion

Here, I have explained what Data virtualization is, its benefits and where this solution fits in an organization also provided information about the most popular data Virtualization tools on the market. There are many more tools available, so please leave your insights about other tools in the comments section!!!


Further Reading

Topics:
big data, data virtualization, data warehouse, tutorial, virtualization

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