mike
Mike Miranda
October 8, 2015

Why Your Company Should Invest in Data Virtualization

invest virtual dataTwenty years ago a lot of companies fought the “trend” of moving toward email, both for communicating internally and with customers. Nowadays, of course, there’s no question about it. You absolutely must use email or your company will remain in business just long enough to be a laughingstock. Social media is a more recent example. Just about every company should be using it to some degree or another and most of them now understand that, but five years ago, this was much more up in the air. Today, the new innovation you’d be wise to adapt immediately is called data virtualization. Let’s take a closer look at why.

What Is Data Virtualization?

Like so many forms of technology, there are a number of ways you could describe what this type of software does. In simplest terms, though, we’re talking about a method for finding the data your company creates and stores. Obviously, if you can’t search for the information your company makes, there’s hardly any point in making it. Most companies, even many that don’t truly realize it yet, depend on being able to efficiently find their data at a moments notice.

Why Traditional Methods No Longer Suffice

Let’s look at how most companies are currently handling their need for storing and searching for data. Some of this may look familiar to you. Chances are most have their data stored in a fairly haphazard way. This could be for a lot of reasons, but it’s probably because the solution for storage has changed over the years. Different types of information get stored because of their unique formats in different ways too. As such, when you conduct a search, it may need to be done across multiple locations and even in a few different ways.

This definitely doesn’t scream “convenience”, much less “efficiency.”

No matter how it’s done, some type of data movement is necessary, which is always clumsy by today’s standards. Data replication may have to be done as well. For a lot of companies, their searches rely on intermediary servers and/or connectors too. No matter which one resonates, if your company is doing this kind of thing for point-to-point integration, there’s a much better way you should know about.

Big Challenges on the Horizon

Even if you’re fairly happy with your current methodology, the truth is that it can’t last for much longer. While it may get the job done now, there are at least three factors that may finally put a nail in its coffin. There could be other elements unique to your industry as well, but let’s look at these three main advantages of data virtualization.

The first is fairly simple, customers won’t tolerate it. Although it may not be true that the customer is literally always right, this time they’re onto something. If their transaction demands data to facilitate it, they’re not going to understand why there’s a holdup. If they have a question about their account or a service you offer, again, having to wait on data is going to seem very strange to them. Think about it: they use search engines every day. While this is definitely a simpler type of search, it’s one they’re very familiar with. Sure, their understanding might not be taking the complexity of your needs into consideration, but that will hardly keep them from judging your business for being slow.

Second, the amount of information your company produces is only going to continue growing in size. This is true for every business, of course. The term Big Data refers to this concept. Not only will you produce more data next year than you are right now, but it’s going to increase at an exponential rate. You need a better system for managing it than the one you currently have at the moment.

Third, Big Data means big costs. You can’t expect that producing exponentially more data is going to continue with the same amount of overhead. Fortunately, it doesn’t have to break your business either.

A Better Way of Doing Things

If you leverage data virtualization, you’re going to address each of those three issues. They’ll never become problems, yet you’ll be producing better results than ever before with any search you do.

It’s going to use your current mainframe to actually transform it into a virtualization module capable of producing the kinds of searches you need. Not only that, but it can carry out these searches better than anything you’re currently using and much more affordably.

Furthermore, the security features it comes with are superior to what traditional methods bring to the table. The last thing you want to do is come up with an easier way of conducting searches only to make it easier for prying eyes to do so too.

Although that transformation of your mainframe we mentioned may sound confusing, it actually produces a much more streamlined search. Data integration will be far less complex thanks to high-quality virtualization measures. No more point-to-point approaches that are cumbersome, at best, and completely ineffective at worst.

Yet, you won’t need nearly the same amount of resources to carry out your searches. MPS capacity usage will be much lower and that means less TCO (Total Cost of Ownership) too. Despite that, it’s still very possible for non-relational information to be changed over into relational. This is a good way of making sure you’re truly getting your money’s worth with your mainframe.

In the end, virtualization is the only way to address your company’s current store of data and catalog it better going forward as well. At some point, you’re going to have to make the investment or suffer the consequences of watching your competitors take the jump. You might as well just go ahead and make the leap now.

As we’ve pointed out, though, this doesn’t have to be a leap of faith. The power of data virtualization, the security it provides and how easy it is to use makes this a very simple decision. It’s the 21st century; use 21st-century tech for better results.

Has your business made the switch to using virtual data? If so, what are some of the advantages you’ve found? Share with us in the comments below.