Steps for Successful Implementation of Data Virtualization

In the recent years, one technology that has thrived and matured into an industry is virtualization. Data virtualization has also shifted from departmental level to an enterprise-level deployment. It is the solution for solving many problems that have plagued organizational data for years. Many companies adopt data virtualization for the reasons listed below:

  1. Unification of data security all across the company.
  2. Creation of a single access point for both types of data i.e. unstructured and structured.
  3. Enhancement of the work agility of developer teams working on projects related to data integration.
  4. Minimization of the end-user impact caused by changes made in data infrastructure by decoupling of apps and analytics from the physical resources.
  5. Enabling of the heterogeneous joins of data present in different locations.
  6. Delivery of operational data for supporting real-time data requirements.
  7. Creation of a link between relational data and big data sources.

The reasons mentioned above are compelling enough to justify a company’s deployment of data virtualization by open source san software but this deployment can prove to be a serious challenge if it is not implemented with careful planning. Management, performance, data quality and usability can be affected severely if data governance or architecture of such powerful technology is not kept in check.

Data virtualization facilitates an organization into exposing their assets to a wider set of audience with ease and speed. This adds the enterprise perspective to the equation of data virtualization. If you are thinking about getting data virtualization deployed in your organization then we will recommend that you follow the five best steps that lead to its successful implementation:

  1. Architect

Data virtualization solutions are evolving every day with the constantly changing requirements of organizations and their users. Data virtualization can become challenging as the number of layers and objects increases. It also leads to low performance and less agility. It is, therefore, crucial that the architect, logic, and dependencies of the business should be carefully evaluated and analyzed before implementation.

  1. Coordination with the Data Governance organization

Data virtualization ideas, concepts, and benefits should be made common knowledge among the people in your data governance organization so that the business rules, processes, standards and data definitions created or changed are in accordance with them. Data virtualization should be governed as a corporate data asset by these organizations.

  1. Usage guidelines

There should be clearly defined guidelines regarding the use of data virtualization technologies in an organization. This helps in making rules for when to utilize traditional methods for accessing data versus virtualization methods. The data developers should also have basic trainings about the capabilities of data virtualization and this technology should be at the top of the list of any initiative related to data development.

  1. Organizational responsibilities

Data virtualization has countless benefit, such as its ability to deploy web services and query based operational systems and providing data for analysis in integrated form. This leads to a conflict where determining who is responsible for the support aspect of this platform becomes a daunting task. Organizational responsibilities related to data virtualization should be clear from the start.

  1. Information Security

Companies all around the world want their data to be secure. This is why data security in data virtualization security should have a strong impact. The risk of data and its sources being exposed to unauthorized users is higher when it comes to data virtualization which is why regulations related to data security should be implemented accordingly.

Conclusion:

From the five reasons listed above, it is quite clear the role enterprise perspective can play in the successful implementation of data virtualization. If left unchecked then data virtualization can become a serious challenge for an enterprise’s IT department. The balance between data architecture and management structure is the key for successful deployment of an organization.

If you are thinking of getting the technology of virtualization in your organization then you should opt for Virtual SAN. VSAN is perfect for companies with existing servers and those who want to reduce CapEx and OpEx related expenses. This VSAN guarantees high performance and low downtime with commercial hardware that is off the shelf.

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