The hype data virtualization technology created over the years has made businesses, enterprises, and data centers keep an eye on it. Major IT service company are keen at providing data virtualization and cloud computing solutions as a computer storage solution to businesses of all kinds and sizes.
But what exactly is Data Virtualization? What are its benefits? How can businesses implement it in their business? Find out here:
DV is an application that enables enterprises to eliminate troubles associated with data analytics. By allowing mapping and consolidation of multiple data assets and sources through a virtual layer, it provides unified access to all the data. Mostly all data virtualization products are utilized to construct, run and manage IT services that are offered by IT services Company. The solutions offered through virtualization are much faster than the traditional ETL approaches.
How does it work?
The process of data virtualization starts with the installation of virtualization middleware that is compatible with the existing infrastructure. The data is made accessible through distributed sources like IoT, cloud, big data and traditional storage system. After this, the data engineers use data design and analytics tools to create desired IT data solutions for business.
What are the known benefits of data virtualization?
With the help of data virtualization, businesses can easily and economically integrate data in this ever-evolving business environment. This virtualized data can be used for a myriad of functions like analytics, business intelligence, and transactional work and support various lines of businesses and projects at once. Since businesses of today rely on up-to-date data for success, it provides updated data through advanced performance optimization algorithms. Moreover, DV ensures that the organizations meet SLAs for reliability, scalability, and security.
Where it’s used?
Data virtualization technology can be used in many places. If the need of business is higher performance speed, DV offers it through IT-grade datasets that allow functions to complete within hours instead of days.
If a business needs to run multiple services, DV technology supports multiple-application data solutions by drawing data sources from shared data systems and saves the time and money to develop it. Furthermore, by sharing data which are frequently used and, it improves data quality.
At places where there is a need for up-to-date data, DV allows businesses to churn fresh data. Additionally, data virtualization helps businesses by providing easy access to the data even if there is no adequate data consolidation in place.
Where it’s not used?
But data virtualization cannot be used everywhere. It is probably not an answer to all the requirements of data analytics. Moreover, the efficiency of data virtualization is significantly affected by the complexity of data. Most often, it is best to implement data consolidation along with ETL or incorporate a hybrid solution.
What’s the point?
Data virtualization is a compelling solution for businesses and enterprises. The solution it offers like real-time access to data is helping business to manage business risks and reduce penalties. Projects that are mostly dependent on data can be completed faster at much lower cost. It has also improved how businesses utilize their servers and storage systems and optimize their functioning.