Putting Data at the Center of IT Infrastructure

The volume and the importance of data are growing, and the generation of it is multiplying at an astounding rate. The challenge is that much of this data is being created at the edge of the network, and in general, IT infrastructure has not been built to handle the increased flow of data back to a central hub for processing.

For data to be at the center of business, it should also be at the center of IT infrastructure. But instead, infrastructure has been built over time, with data siloed by application, line of business, or time elapsed. Data also has gravity, and moving it from the edge to a processing hub becomes more difficult as its heft increases. It may be a challenge to move it to the cloud as well, making real-time data value impossible.

Where this often impedes enterprises is at the point of artificial intelligence (AI) technology, which when granted real-time access to data, has the ability to analyze data and use it to create new opportunities. Fragmented infrastructure is the opposite of what enterprises are trying to achieve with cloud solutions (scalability, agility), so many are considering what it takes to create an IT infrastructure that is data centered. Here are the critical elements:

Consolidation: In order to make data available for real-time analysis and insights, it must be removed from data islands and placed in a bigger storage pool. This is not only good for agility and scalability but also lends itself to a more simplified security approach.

Real-time access: Data is at the center of your business strategies, but is it good, up-to-date data you’re working with at decision time? Your infrastructure design must prioritize real-time access to data.

Self-driving: An efficient data-centered IT infrastructure doesn’t require a dedicated team to monitor storage management. You need to include automation that eliminates much of the administration and creates standard services and standard application programming interfaces (APIs) that remove manual tasks from your team.

Multi-cloud: Even if your organization hasn’t completely embraced a cloud-first strategy, it’s a good idea to plan ahead for cloud migration. Your best planning involves a multi-cloud approach; one that’s easily tailored to both private and public cloud for data storage, data processing or easy access to data for cloud solutions to tap into it.

Forward-facing: One of the most critical elements to your approach to data is simply that it’s not created for the past, or even the current, role of data in business. Think ahead in terms of AI and how data can shape your enterprise’s path in the future.

When it’s time to restructure your environment for data-centered infrastructure, contact us at TailWind. We help you navigate cloud migration and infrastructure decisions with certified, on-site technician support for a seamless transition.