Big Data science analysis business technology concept on virtual screen.
Data virtualization is a stepping stone between gathering data and turning that data into useful information. Just as binary machine code is incomprehensible to most people, you usually aren’t going to find raw data straight out of a data table useful by itself. If you need to figure out a way to turn a camera or smoke detector into a computerized input that means something, data virtualization software is the way to go. If this sounds interesting to you, here’s some more info for you to consider.
Data Virtualization
What is data virtualization, then, and why is it helpful? Well, having all the details is important but having them all the time might not be practical. Data virtualization can be used to solve the problem of information overload when you need to analyze data from one or more sources, and this can be more helpful than you might expect. Its purpose is not to provide less information, but rather to be a software optimization solution that provides critical information when and where you need it.
This means that individual people can interact with complex databases in a single specific way without worrying about accidentally finding the wrong information or supplying important information to the wrong location. If you need to make sure your data is updated to the minute while also staying true to disparate data sources, data virtualization is what you need.
Hardware Input
Many practical applications of data virtualization involve input from an end-user or some other stimulus that incites a reaction from a piece of software. If you are looking for refurbished cell phones, for example, then you might be offered a different kind of phone depending on where the website thinks you live, analytics regarding what kind of refurbished phone is in stock, and what phones are selling the most.
You might be offered a warranty that best suits these details as well, and all of these decisions would be made using real-time data and brought to you in a specific way through a single point of access. Data virtualization is a very infrastructure-heavy way of sending high-quality data where it needs to go, so if you are interested in using such a software solution for your next business venture this should be taken into consideration as well.
Pros and Cons
There are times when data virtualization is useful, but there are times when you might be served by other data service solutions as well. As mentioned before, data virtualization is useful when you can front the funds required to heavily invest in the required infrastructure, but this isn’t always practical. The technical details involved in unifying heterogeneous data sources are necessarily going to require special attention to detail.
Not all application vendors are capable of supporting data virtualization, either, which means you need to pay close attention when deciding on what your software is supposed to do when you start developing it. That being said, if you manage to get all these pieces to line up you stand to benefit from a faster, more efficient, and cost-effective system overall from an IT standpoint.
Data virtualization is a scalable solution that can be fitted to many problems. Adaptability is the name of the game, and having a way to get data from point A to point B in a transformative way that makes sense for your company is a massive undertaking by itself. That being said, there is a massive amount of data out there to work with and not all of it can be treated the same way and sometimes data virtualization is the best way to make sense of it all.
