There are many technical terms now on the scene and ‘data virtualization’ is another one that you’re likely to hear often.
Data virtualization is a concept within data management whereby it’s possible for an application to retrieve and change data without any technical details.
What does this mean in practice?
It means it doesn’t matter how the source is formatted or where its physical location is. You can get a single customer view. Look at it like this: it’s a way to unify data across all platforms.
So how can this apply to master data management?
How Data Virtualization Builds a Complete Customer View
There are three use cases for data virtualization. In this section we’re only going to talk about two of them because the other relates to master data management virtually.
The first use case is analytical. In this case, you may be drawing master data from a range of data sources. Your so-called data warehouse may have a range of different categories and sources.
What data virtualization does is create a unified view of data drawn from all sources within your organization. You’re getting unity and the complete picture.
There’s also the operational use case. In this case, the so-called data warehouse is irrelevant because the data isn’t being stored for analytical purposes or for historical data to be used in future. Data virtualization combines the data drawn directly from any of the transactional systems within your company.
How Virtual Master Data Management Works
Anyone who follows master data management best practices is aware of the necessity for security. If we look at a classic master data management system, golden records will be stored within a separate database. In certain industries, like healthcare, there are big restrictions when it comes to data replication.
So how can these industries use data virtualization to comply with these restrictions?
Through combining data virtualization with classic master data management systems you can create a virtualization layer that performs the majority of the functions of a master data management system.
You’re only getting a virtual view of the data when you draw everything together. There’s no replication involves, so you don’t lose your agility because you happen to be in an industry with strong restrictions on how you use data.
Does this Add a New Layer of Management to My Data Strategy?
You don’t need to have a huge data division to deliver data virtualization in your organization. There are things to learn, but the complexity of your work doesn’t increase.
See data virtualization as another tool that can be used within your master data management strategy. It’s another option that can be employed when the situation demands it.
Don’t be put off by its apparent complexity. It’s not as difficult as it looks!
Last Word – Implementing Data Virtualization Within Your Company
Data virtualization is a way to further expand how agile you are when it comes to data. When properly integrated within a master data management strategy, you can improve how your company manages data and comply with all industry restrictions.
Are you going to implement data virtualization within your company? Let us know in the comments section below.