The Old Ways of Doing Things
Traditionally, data management has been a cumbersome process, to say the least. Usually, it means data replication, data management or using intermediary connectors and servers to pull off point-to-point integration. Of course, in some situations, it’s a combination of the three.
Like we just said, though, these methods were never really ideal. Instead, they were just the only options given the complete lack of alternatives available. That’s the main reason you’re seeing these methods less and less. The moment something better came along, companies jumped all over them.
However, their diminishing utility can also be traced to three main factors. These would be:
· High costs related to data movement
· The astronomical growth in data (also referred to as Big Data)
· Customers that expect real-time information
These three elements are probably fairly self-explanatory, but that last one is especially interesting to elaborate on. Customers these days really don’t understand why they can’t get all the information they want exactly when they want it. How could they possibly make sense of that when they can go online and get their hands on practically any data they could ever want thanks to the likes of Google? If you’re trying to explain to them that your company can’t do this, they’re most likely going to have a hard time believing you. Worse, they may believe you, but assume that this is a problem relative to your company and that some competitor won’t have this issue.
Introducing Data Virtualization
It was only a matter of time before this problem was eventually addressed. Obviously, when so many companies are struggling with this kind of challenge, there’s quite the incentive for another one to solve it.
That’s where data virtualization comes into play. Companies that are struggling with having critical information spread out across their entire enterprise in all kinds of formats and locations never have to worry about the hardships of having to get their hands on it. Instead, they can use virtualization platforms to search out what they need.
Flexible Searches for Better Results
It wouldn’t make much sense for this type of software to not have a certain amount of agility built in. After all, that’s sort of its main selling point. The whole reason companies invest in it is because it doesn’t get held back by issues with layout or formatting. Whatever you need, it can find.
Still, for best results, many now offer a single interface that can be used to separate and extract aggregates of data in all kinds of ways. The end result is a flexible search which can be leverage toward all kinds of ends. It’s no longer about being able to find any type of information you need, but finding it in the most efficient and productive way possible.
Keep Your Mainframe
One misconception that some companies have about data virtualization is that it will need certain adjustments to be made to your mainframe before it can truly be effective. This makes sense because, for many platforms, this is definitely the case. These are earlier versions, though, and some that just aren’t of the highest quality.
With really good versions, though, you can basically transform your company’s mainframe into a virtualization platform. Such an approach isn’t just cost-effective. It also makes sure you aren’t wasting resources, including time, addressing the shortcomings of your current mainframe, something no company wants to do.
Don’t get turned off from taking a virtualization approach to your cache of data because you’re imagining a long list of chores that will be necessary for transforming your mainframe. Instead, just be sure you invest in a high-end version that will actually transform your current version into something much better.
A Better Approach to Your Current Mainframe
Let’s look at some further benefits that come from taking this approach. First, if the program you choose comes with the use of a high-performance server, you’ll immediately eliminate the redundancy of integrating from point-to-point. This will definitely give you better performance in terms of manageability. Plus, if you ever want to scale up, this will make it much easier to do so.
Proper data migration is key to a good virtualization process. If it is done right the end user wont have to worry out corrupted data and communication between machines will be crystal clear.
If you divert the data mapping you need to do at processing-intensive level and transformation processes away from the General Purpose Processor of your mainframe to the zIIP specialty engine, you’ll get to dramatically reduce your MIPS capacity usage and, therefore, also reduce your company’s TCO (Total Cost of Ownership).
Lastly, maybe you’d like to exploit of every last piece of value you derive from your mainframe data. If so, good virtualization software will not only make this possible, but do so in a way that will let you dramatically turn all of your non-relational mainframe data virtualization into relational formats that any business analytics or intelligence application can use.
Key Features to Look for in Your Virtualization Platform
If you’re now sold on the idea of investing in a virtualization platform, the next step is getting smart about what to look for. As you can imagine, you won’t have trouble finding a program to buy, but you want to make sure it’s actually going to be worth every penny.
The first would be, simply, the amount of data providers available. You want to be able to address everything from big data to machine data to syslogs, distributed and mainframe. Obviously, this will depend a lot on your current needs, but think about the future too.
Then, there’s the same to think about in terms of data consumers. We’re talking about the cloud, analytics, business intelligence and, of course, the web. Making sure you will be able to stay current for some time is very important. Technology changes quickly and the better your virtualization process is the longer you’ll have before having to upgrade. Look closely at the migration process, and whether or not the provider can utilize your IT team to increase work flow. This will help you company get back on track more quickly and with better results.
Finally, don’t forget to look at costs, especially where scalability is concerned. If you have plans of getting bigger in the future, you don’t want it to take a burdensome investment to do so.
As you can see, virtualization platforms definitely live up to the hype.You just have to be sure you spend your money on the right kind.
Guest blogger post :
Introducing Data Virtualization
It was only a matter of time before this problem was eventually addressed. Obviously, when so many companies are struggling with this kind of challenge, there’s quite the incentive for another one to solve it.
That’s where data virtualization comes into play. Companies that are struggling with having critical information spread out across their entire enterprise in all kinds of formats and locations never have to worry about the hardships of having to get their hands on it. Instead, they can use virtualization platforms to search out what they need.
Flexible Searches for Better Results
It wouldn’t make much sense for this type of software to not have a certain amount of agility built in. After all, that’s sort of its main selling point. The whole reason companies invest in it is because it doesn’t get held back by issues with layout or formatting. Whatever you need, it can find.
Still, for best results, many now offer a single interface that can be used to separate and extract aggregates of data in all kinds of ways. The end result is a flexible search which can be leverage toward all kinds of ends. It’s no longer about being able to find any type of information you need, but finding it in the most efficient and productive way possible.
Keep Your Mainframe
One misconception that some companies have about data virtualization is that it will need certain adjustments to be made to your mainframe before it can truly be effective. This makes sense because, for many platforms, this is definitely the case. These are earlier versions, though, and some that just aren’t of the highest quality.
With really good versions, though, you can basically transform your company’s mainframe into a virtualization platform. Such an approach isn’t just cost-effective. It also makes sure you aren’t wasting resources, including time, addressing the shortcomings of your current mainframe, something no company wants to do.
Don’t get turned off from taking a virtualization approach to your cache of data because you’re imagining a long list of chores that will be necessary for transforming your mainframe. Instead, just be sure you invest in a high-end version that will actually transform your current version into something much better.
A Better Approach to Your Current Mainframe
Let’s look at some further benefits that come from taking this approach. First, if the program you choose comes with the use of a high-performance server, you’ll immediately eliminate the redundancy of integrating from point-to-point. This will definitely give you better performance in terms of manageability. Plus, if you ever want to scale up, this will make it much easier to do so.
Proper data migration is key to a good virtualization process. If it is done right the end user wont have to worry out corrupted data and communication between machines will be crystal clear.
If you divert the data mapping you need to do at processing-intensive level and transformation processes away from the General Purpose Processor of your mainframe to the zIIP specialty engine, you’ll get to dramatically reduce your MIPS capacity usage and, therefore, also reduce your company’s TCO (Total Cost of Ownership).
Lastly, maybe you’d like to exploit of every last piece of value you derive from your mainframe data. If so, good virtualization software will not only make this possible, but do so in a way that will let you dramatically turn all of your non-relational mainframe data virtualization into relational formats that any business analytics or intelligence application can use.
Key Features to Look for in Your Virtualization Platform
If you’re now sold on the idea of investing in a virtualization platform, the next step is getting smart about what to look for. As you can imagine, you won’t have trouble finding a program to buy, but you want to make sure it’s actually going to be worth every penny.
The first would be, simply, the amount of data providers available. You want to be able to address everything from big data to machine data to syslogs, distributed and mainframe. Obviously, this will depend a lot on your current needs, but think about the future too.
Then, there’s the same to think about in terms of data consumers. We’re talking about the cloud, analytics, business intelligence and, of course, the web. Making sure you will be able to stay current for some time is very important. Technology changes quickly and the better your virtualization process is the longer you’ll have before having to upgrade. Look closely at the migration process, and whether or not the provider can utilize your IT team to increase work flow. This will help you company get back on track more quickly and with better results.
Finally, don’t forget to look at costs, especially where scalability is concerned. If you have plans of getting bigger in the future, you don’t want it to take a burdensome investment to do so.
As you can see, virtualization platforms definitely live up to the hype.You just have to be sure you spend your money on the right kind.
Guest blogger post :
Mike Miranda writes about enterprise software and covers products offered by software companies like Rocket software about topics such as Terminal emulation, Enterprise Mobility and more.
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