Friday, 4 September 2015

The Importance of Data Virtualization

It’s been a long time since the way data was stored and accessed has been addressed. We went from scrolls to books to mainframes and this last method hasn’t budged all that much over the last decade or so. This is despite the fact that we keep creating more and more information, which means that better ways for storing and finding it would make a world of difference. Fortunately, this is where data virtualization comes into play. If your company isn’t currently using this type of software, you’re missing out on a better way of leveraging your organization’s data.

Problems with Traditional Methods

No matter what line of work you’re in, your company is creating all kinds of information each and every business day. We’re not just talking about copy for your website or advertising materials either. Information is created with each and every transaction and just about any time you interact with a customer.

You’re also not just creating information in these moments. You need to access stored data too. If you don’t do this well—and many, many companies don’t—you’re going to end up with a lot of unnecessary problems. Of course, you’re also wasting a lot of money on all that info you’re creating but not using.

The main problem with traditional methods of data storage and retrieval is that they rely on movement and replication processes and intermediary servers and connectors for integrating via a point-to-point system. This worked for a long time. For a few companies, it may seem like it’s still working to some degree.

However, there’s a high cost to this kind of data movement process. If you’re still trying to shoulder it, chances are your overhead looks a lot worse than competitors that have moved on.
That’s not the only problem worth addressing, though. There’s also the huge growth of data that’s continuing to head north. We’ve touched on this, but the problem is so prevalent that there’s a term for it throughout every industry: Big Data. Obviously, it refers to the fact that there is just so much information out there, but the fact this term exists also shows how much it affects all kinds of companies.

Big Data is also a statement about its creation. Its sheer proliferation is massive. Every year, the amount increases at an exponential rate. There’s just no way the old methods for storing and finding it will work.

Finally, customers expect that you’ll be able to find whatever information you need to meet their demands. Whether it’s actual information they want from you or it’s just information you need to carry out their transaction, most won’t understand why this isn’t possible. After all, they use Google and other search engines every day. If those platforms can find just about anything for free, why can’t your company do the same?

The Solution Is Data Virtualization

If all of the above sounded a bit grim, don’t worry. There’s a very simple solution waiting for you in data virtualization. This type of software overcomes the challenges that come with your data being stored all over your enterprise. You never again have to run a million different searches to collect it all or come up with some halfway decent workaround. Finally, there’s a type of platform made specifically for your company’s data gathering needs.
This software isn’t just effective. It’s convenient too. You work through one, single interface and can have access to the entirety of your company’s data store. What it does is effectively separate the external interface from the implementation going on inside.

How It Works

Every data virtualization platform is going to have its own way of working, so it’s definitely worth researching this before putting your money behind any piece of software. However, the basic idea remains the same across most titles.
With virtualization software, the data doesn’t have to be physically moved because this technology uses meta data to create a virtual perspective of the sources you need to get to. Doing so provides a faster and much more agile way of getting to and combining data from all the different sources available:
·      Distributed
·      Mainframe
·      Cloud
·      Big Data
As you can probably tell, this makes it much easier to get your hands on important information than the way you’re currently doing it.

Finding the Right Title for Your Company

Although they all serve the same purpose and the vast majority will follow the outline we just went through, there are still enough virtualization software titles out there that it’s worth thinking about what your best option will look like. As with any type of software, you don’t want to invest your money anywhere it’s not going to do the most good.
The good news is that this software has been around long enough that there have been best practices established for how it should work.
First, you want to look for a title that will actually transform the way your mainframe works by leveraging what it can do for every search. This is just a good use of your resources and gives you more bang for your buck as far as your mainframe is concerned. Software that uses it for virtualization purposes is going to work even better than a distribution-based application and won’t cost any more.

However, it’s also going to work a lot better for that price too. A lot of companies also love that this way of carrying out a search is more secure as well. The last thing you want is to pay for a piece of software that’s actually going to leave you worse off.

Secondly, although this may sound complex, you can and should find a solution that keeps things simple. Data integration can be straightforward with the method we just described without any need for redundant processes that would slow down your ability to scale up.

With data virtualization, there is no downside. Furthermore, it’s becoming more and more of a necessity. Companies are going to have to invest in this software as Big Data continues to get bigger.



Mike Miranda writes about enterprise software and covers products offered by software companies like Rocket Software.about topics such as Terminal Emulation, Legacy Modernization, Enterprise Search, Big Data and Enterprise Mobility.


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