Blog: Your Infrastructure Isn’t the Problem, Your Data Access Is (Part 2)

Part 2: The Answers Have Changed, and there are Modern Solutions

Precursor: Are you asking yourself, “the answers to what have changed?” If so, check out Part 1 here.

The Shift from “That’s Just How It Is” to “What If You Didn’t Have To?”

Organizations are starting to realize that the traditional way of moving, prepping, and altering data before it can be used no longer fits the scale and speed demanded by today’s workloads—especially in AI, cloud, and edge environments.

If the way you create (e.g. IoT, etc.), store (e.g. datalakes, etc.) and use (e.g. AI, etc.) your data can—and have—changed… isn’t it about time to the way you move and access it should do the same? And we’re starting to see that. There’s been a perception chang e from “delays are an annoying but accepted part of working with distributed datasets” to “I see those delays are starting to compound and that’s going to be problematic” to “okay, maybe there are alternatives to running cutting edge AI and analytics programs while simultaneously relying on data transfer and storage that’s been around for almost a half century.”

This mental shift in customer discernment is opening the door for organizations to be more preemptive in their IT strategies: by realizing modern solutions can unlock new levels of agility, speed, and opportunity that was never possible. If the way you create (e.g. IoT, etc.), store (e.g. datalakes, etc.) and use (e.g. AI, etc.) your data can—and have—changed… isn’t it about time to the way you move and access it should do the same?

Today, you can create an enterprise-grade, continuous data pipeline to and from anywhere. That’s due to a change in the way you access your data: leaving it where it is currently stored (say, the edge or in the cloud) and allowing your application or user—who could be thousands of miles away—to access just the pieces of information you need from afar.

What’s that actually mean? Let’s take our scenarios identified in Part 1, and evaluate how a modern solution could change the situation and outcome:

The Old Answer

 

The New Answer

AI/ML teams waiting hours—or days—for datasets to arrive… or moving ahead with stale or incomplete data

Teams interact with data as soon as it’s created, even from thousands of miles away, enabling near real-time training, inferencing, and tuning

Data engineers stuck collaborating on multiple file versions

Teams work from a single, centralized version to drastically reduce time to market

Cloud projects running over budget and behind schedule due to inflated storage costs and transfer times

Projects are completed months sooner, avoiding storage bloat (unnecessary copies) and transfer costs between regions and/ or clouds/ prem

Skyrocketing budgets and complexity due to building multiple data centers to provide an acceptable level of performance to distributed teams

Data storage stays centralized, while still offering local-like access anywhere, enabling you to build a single data center instead of many, with a single set of infrastructure

 

If a New Answer Exists, Why are we doing it the old way?

Many of us may remember the days of going to a store filled with rows of movies to rent. Then we could go to a vending machine to get movies or have them delivered to our mailboxes. Now, we can stream them on-demand.

If you can get the latest movie to watch instantly at home—how come you need to wait until tomorrow to access the file your global team sent you at lunch?

The truth? Many people don’t believe this kind of data access is possible.

For decades, we’ve accepted the idea that data must be physically moved to be used. That processing must happen where the data resides. That duplicating data or infrastructure to manage regulatory or operational needs were just the cost of doing business.

But that’s no longer true.

Modern technology enables data to be accessed instantly and without moving it—even from thousands of miles away. This is gamechanger:

  • Faster time-to-insight and action: Analyze data as soon as it’s created or across edges, expanding reach and delivering near real-time analytics
  • Secure, easier compliance: Whether you’re talking PII, HIPPA, GDPR, or one of the myriads of other regulatory or compliance requirements, support adherence by maintaining just a single dataset and allow secure access to it while it stays in situ
  • Drastic CAP/OPEX reductions (and smarter investments): Instead of building and maintaining multiple data centers (and associated infrastructure) to provide performance to local teams, enable local-like experiences from a single, potentially more distant, data source
  • Easier, more agile data storage and governance: Avoid storage bloat, egress charges, and versioning mishaps by maintain a single, globally-accessible dataset

 

Rethinking how you interact with your data.

It’s time to break decades of ingrained thinking… challenge the impossible. While the future may be about more data, more quickly… it’s not necessarily about more data centers or more storage. It’s about smarter data access—rethinking the way you interact with your data.

Those who do will unlock faster innovation, stronger customer outcomes, and greater competitive advantage. The technology is here, and the possibilities are real. It’s up to you whether you take it advantage of it.