A Complete Guide to Data Virtualization for Business

Companies are actively looking beyond traditional data integration capabilities such as Extract Transform Load (ETL) systems or data warehouse software as they acquire large volumes of diverse data from a growing number of sources. Here's a complete guide to data virtualization for business.

Enterprises are deploying data virtualization technology solutions to meet the growing demand for data for multiple purposes, from faster provisioning of new data to self-service data access for customers. It is extremely useful for data consumers, IT and technical teams.

Data virtualization is a mature technology

Data virtualization is a mature technology currently used as part of an enterprise's data integration strategy. According to MarketsandMarkets, the data virtualization market size is expected to reach USD 1.58 billion in 2017. Further, it is expected to reach USD 4.12 billion by 2022, at a compound annual growth rate (CAGR) of 21 .1% over the forecast period (2017 to 2022).

Data virtualization technology creates a logical extraction layer

Data virtualization technology creates a logical mining layer in the processing of distributed data management. It allows users to access data of any format and heterogeneous source (data warehouse or data lake) in a standardized way.

As a result, data users do not need to worry about the technical aspects of the data, such as where and how the data is stored, the type of data and its storage structure, and the interface of the original source of data storage, etc.

Furthermore, this data is consumed through virtual views by applications, query/report tools, message-oriented middleware, or other data management infrastructure components.

How does data virtualization work for a business?

Companies can easily access the data they need with data virtualization. A three-step process is involved in implementing data virtualization:

Connect: Data virtualization connects to various data sources i.e. databases, data warehouses, cloud applications, big data repositories and even Excel files.

Combine: Data virtualization combines and transforms related information or date of any format into views or business information.

Deliver: Data virtualization accesses real-time data and delivers it to businesses through reports, dashboards, portals, mobile apps, and web apps

While data virtualization technology combines various data sources into a single user interface, the virtual or semantic layer is at the heart of the technology. It allows data or business users to further organize their data into different virtual schemas and virtual views in any format and from any source.

Users can access all unified data from various systems through the virtual layer, which produces a single consolidated data source. This information is safe and secure and complies with all industry requirements.

Users can easily enhance this virtualized data to prepare it for analysis, reporting, and automation procedures.

Why do you need to virtualize data?

These factors explain the growing importance of data virtualization:-

Responds to Data Requests: As companies continue to undertake analytics and use self-service analytics tools, data requests from business and data analysts, scientists and engineers to edge can become unmanageable. The results help businesses make better decisions and delight their customers. Therefore, data virtualization allows you to view all your real-time data from a single, centralized location. This allows scans to complete faster than usual.

Manage data complexity and volume: The quest for rapid expansion has increased the number of unconnected physical databases and complex data in enterprises. The fastest way to combine them for analysis is to use data virtualization.

The rate of data generation is clearly increasing, making it difficult to update a physical data warehouse. Additionally, data virtualization is a more advanced method of transferring data from multiple locations.

Delivers data agility: While giving business users a self-service option can be a priority, enterprises are constantly striving to strike the right balance between strong security and agility of the company. Data virtualization makes all enterprise data accessible to different users.