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The Advantages of Data Virtualization


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4 min read

virtual dataIt’s hardly any secret that the growth of data isn’t going to head in the other direction anytime soon. Instead, we’re only going to see more and more of it. In fact, the trend is actually that we’re going to see even more data being produced on a regular basis. That is, the growth of information is increasing at an exponential rate. As such, it would make sense for your company to take steps to prepare for this kind of future. If you’re not already using data virtualization software, now would be the time to make that investment. Not only will it make a big difference, but the sooner you begin using it, the sooner it will become like second nature in your organization.

What Is Data Virtualization Software?

Virtualization refers to software meant to help make sense of the massive amounts of data most companies have to deal with these days. The main problem involved, which this software is made to address, is twofold. First, there’s the fact that a lot of businesses have been collecting data for years and years, meaning the ways they do so and how they store this information have both changed dramatically.

It’s very difficult for a company to reconcile the different ways data gets collected. Over the years, the location where the same type of data gets stored could change. The very format used could be different as well. As a result, it’s not like you can do a simple search and always get all the information you need. Instead, you’ll probably have to do a number of different searches and hope for the best or take a lot of time to run a comprehensive one.

Obviously, neither approach is confidence-inducing. The thing is, though, most customers—in both B2C and B2B contexts—aren’t going to wait on you. To them, it doesn’t make sense why you can’t find the information they want and provide it to them immediately. After all, they most likely don’t know about the way searches work inside an organization. They just know Google, and Google can find anything in a matter of seconds.

How This Software Provides an Opportunity

Of course, this kind of thing makes for quite the opportunity too. It means that you have the ability to outdo your competitors by leveraging data virtualization software to help you get a hold of any information customers may be asking for or which may otherwise help keep them satisfied.

Data retrieval isn’t all about customers, though. A lot of the processes you need to go through to succeed as a company will only work if you’re able to go out and grab the vital information you’ve compiled. Considering scaling up, for example? You won’t know if this is truly a possibility or even a good idea if you can’t extract certain pieces of information first and look through your history.

Furthermore, a lot of users are surprised to find out that they can actually leverage their software for the purpose of transforming their mainframe into a virtual environment where non-relational and relational elements can work with one another without all the typical issues getting in the way.

Data Virtualization Will Save You Money

What’s more, virtualization platforms can do much more than just provide you with ample opportunities. They won’t just solve the problem of efficiently harvesting data either.

There’s another important problem that this type of platform can help with and that’s saving your company money. Obviously, having use of all the information your company has produced will help keep more money in your budget.

However, think about all the ways you’re currently hemorrhaging money because of the fragmented way with which you store your data. Many of your employees are probably giving up before they run the most comprehensive searches possible. Others may be using substandard workarounds.

Those who are able to patch together some type of protocol that launches a complete search are going to be wasting a lot of time—and thus money—doing so.

With virtualization software, all these frustrating, unnecessary problems are firmly in the past where they belong.

Use Better Analytics

It’s even a bit shortsighted to only think of the kinds of searches this type of software can pull off despite the fact that this is expressly what it was made for. Instead, you should also think about the analytics that will be available to you as well.

Better analytics come about from better data compilation at the beginning of the process. Any time information is created within your company, it should immediately be marked for the sake of organization. That’s what this type of software can do, so that later on, when you need to run analytics for some reason, you’re able to do so without issue.

Organizing Your Current Data

What about the data you’ve already created? You might be wondering about what to do with this information so analytics can get a hold of it. Virtually integrating it so that you have it all in one place is the way to go and exactly what this software does. It’s really as simple as that.

In the past, mainframes made this almost impossible to do. Usually, companies have used something like the ETL (Extract, Transform, and Load) method for handling this. If yours has been doing this, then you already know all about its shortcomings. The main one is that extracted data has to be transformed and then loaded, which keeps it from being current. That right there destroys one of the most important advantages of incoming information, which is timeliness.

Finding the Right Platform

If you’re sold on virtualization, then the next step is actually investing in a platform. With so many options out there, though, this can be easier said than done. Just look for one that comes with a sizable breadth of providers and consumers as far as data is concerned. It should be able to integrate DB2 applications and provide real-time performance.

As long as companies will continue creating huge amounts of information on a regular basis, data virtualization software will be essential.

Does your business use data virtualization in daily operations?

Originally published Sep 30, 2015, updated Aug 12, 2020

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