Businesses and people are constantly looking for the cutting edge, the mainstream or the current trend. They’ve come to expect it. So, it isn’t surprising that as we’ve become more integrated with technology and information, we expect the data we digest to be up-to-the-minute accurate.
This is where data virtualization comes into the picture.
Data virtualization is a way of bringing a real-time perspective of data to the world. As technology and networking have advanced, data virtualization has created an almost instantaneous stream of information. This pertains to data of all types: remote, structured, unstructured, local, and transient.
There are several layers that go into how the data virtualization process works. The three different areas that comprise this model would be data consumers, data virtualization servers, and data sources.
The are several entities that can be considered a data consumer, and these typically get categorized into three distinct groups.
Business Intelligence Tools are tools used by corporations to optimize performance, revolutionize standards, and move the company forward. These data virtualization tools help them understand market trends, consumer habits, and where the industry might be heading. Businesses have come to rely heavily on data virtualization to be competitive in the 21st century.
Direct Users are the individuals out there who need to understand complex data and material in a virtual way. Often used for individual understanding or advancement, data virtualization provides specific information for the direct user’s individual needs.
Applications can be found on your tablets, smartphones, and computers. These provide search engines, live analysis, and a wealth of other applications. They offer a wide range of data virtualization at the touch of a button.
Data Virtualization Servers
Servers provide a vital role in the virtualization process. They access data sources and stores. These can be from a local file to public information available on the cloud. They use these stores and bring them together to create common views. They are the funnel through which all of the information flows.
Data servers are the molding process for virtualization. The identity of the consumer will influence how the relevant data is sculpted and virtualized. Servers must be flexible and adaptive to both the fluctuating data source and consumer.
Just like with data consumers, there are several different types of data sources. Data sources are exactly what their name implies — information stores that act as the source system for information. It is where the analysis query is located. These can range from small scale information stores to globally accessed databases.
Data warehouses are collections of data from a variety of different levels of abstractions. Spreadsheets create ranges in a variety of programs. Document management provide trends and analytics attained across numerous documents and files. Web content and social media refers to applications across the internet. Cloud data and applications provides information collected across various applications and server stores. Data and applications in relational databases are designed to give the user an experience with a layer of abstraction with their table.
All of these sources are used to produce varying types of data virtualizations. They can be referenced and cross-referenced in numerous ways to provide the servers with the information they need to create products for the consumers.
As the world becomes more interconnected and technologies continue to advance, understanding how these three layers of virtualization interact will be key in keeping the information fresh. Software companies will continue to streamline information both to businesses and individuals seeking to incorporate these real-time market analysis into their lives. Data virtualization will be how the world understands these diverse abstractions.