Many employees in IT firms are familiar with the data virtualization concept and methods. There is one typical example of using data virtualization, i.e., let’s say you upload your photos on Facebook where you need to upload the picture from a personal computer source. You will provide the upload tool with the file path of the images.
After you upload your photos on Facebook, you can get back your pictures without knowing your picture's new file path. Facebook is filled with a data virtualization abstraction layer that secures its technical information. The coating is meant to be known as data virtualization.
When companies want to build data virtual data services, they have to follow the three steps given below:
Connect and source virtualization: A quick access to the desperately structured or unstructured data sources using the connectors. They would have to bring the metadata on board while creating a regular source view in the data virtualization layer. Combine and integrate into your business data views: Integrating data views and transforming the source views into typical business data views. A scripted or GUI environment can achieve the transformation of data views. Publish and secure your data services: To publish and connect the data views into SQL based on a dozen reliable data formats.
When the DV environment is in its place, the users will accomplish the tasks using the integrated information. The DV environment allowed to search with information discovery from various streams. These varied streams are metadata, hybrid query optimization, integrated business information, data governance security, and service level policy. Each of these streams has its functions with DV layers.
Data Virtualization Tools
Data virtualization offers the delivery of the data through new and faster methods while obtaining integrated information from various sources. These are the top data virtualization tools that the companies use:
Data virtualization is beneficial for the companies using it can quickly combine multiple data sources with the improvement in productivity in information technology by the business data users (50-90%) while accelerating the time based on a value. In addition, data virtualization also improves the data quality with data latency, remove the cost associated with data warehouse maintenance, and reduce multiple copy need, resulting in less hardware infrastructure.
Many people consider data virtualization as visualization, but visualization is about displaying graphical data to the users. The companies use data visualization software to practice combining data with brand-specific narratives with storytelling methods that resonate with the customers to market a product or brand. Multiple companies use enterprise analytical platforms to get assistance within the three areas of data analytics with its definition, tracking, and understanding.
"Zetaris" is a company that provides services related to big data analytics to get you to make informed decisions based on data visualization and virtualization.