Security and Governance
A requirement for robust security and governance measures across diverse data sources can be efficiently managed through a data virtualization layer. This centralises access control, encryption, and audit capabilities.
Key Considerations to Successfully Implement Data Virtualization
Neglecting the reason for data virtualization
It’s really important to first get a handle on what your business actually wants to achieve and what the end users need. If you skip this step, you’re risking time and resources on a system that might not be usable by the people it was designed for. Don’t forget, this isn’t a one-person show. You’ll want your IT department, your data governance team, and your business units all pulling in the same direction.
Poor communication = useless data virtualization
Communication is key here. A lack of chat between the people setting up the system and the ones using it can lead to some head-scratching moments when it doesn’t do what it’s supposed to. And speaking of expectations, data virtualization is cool, but it’s not a magic wand. It can’t fix every data issue you’ve got, so be realistic about what it can and can’t do.
Increased network traffic
On the techy side, keep an eye on network traffic. Pulling data in real-time from all over the place can clog up your network, so be mindful of that. And make sure someone’s actually in charge of keeping the system up and running. Nothing brings the house down faster than a system crash with no one to fix it. Being aware of these pitfalls can help you navigate the tricky waters of data virtualization a bit more smoothly.
So where do Amplifi come in?
Amplifi data expertise is not just limited to data integration or virtualization.
We have the capability to support you from start to finish all along your journey to a modern data ecosystem. Ultimately there’s a lot more that comes along with that, things like your governance, your data quality and your data strategy.
We’re data people who think in a way that you need us to. We want to make sure your data journey is a seamless one and continues to be supported post implementation.