The promise of artificial intelligence (AI) is echoed across nearly every industry, fueling everything from innovation pipelines to operational overhauls. But here’s the kicker: despite all the buzz, most of these ambitious AI and data projects don’t make it past the finish line. In fact, some reports peg the failure rate at up to 80%, costing businesses a jaw-dropping $100 billion annually.
Key Takeaways:
- Up to 80% of AI and data projects fail, costing over $100 billion each year.
- Failures often stem from complicated data management and limited resources.
- Most organizations operate across multiple storage platforms; over half use all four types.
- Hitachi Vantara’s EverFlex AI Data Hub as a Service aims to resolve these data woes.
- It provides a unified platform for AI, BI, and data operations, enhancing quality and governance.
So what’s dragging things down? It often boils down to tangled data management, not enough resources, and the overwhelming complexity of handling data sprawled across multiple platforms. Picture this: an enterprise juggling on-premises servers, private clouds, hybrid clouds, and public clouds—it’s chaos. This kind of fragmented setup leads to what some have aptly called a “litany of AI data preparation challenges.”
Now, Hitachi Vantara—a subsidiary of Hitachi, Ltd.—is stepping in with something that might just shift the game. Their new offering, the Hitachi EverFlex AI Data Hub as a Service, is designed to cut through the noise. It’s a fully managed, all-in-one infrastructure service specifically built to untangle the mess of AI data preparation. It leans on a modern data lakehouse architecture and folds in integrated tools for AI, business intelligence (BI), and just about every other data-driven initiative you can think of.
What’s clever here is the flexible pricing model: you only pay for the infrastructure you actually use. And since it runs on a hybrid cloud model, you still retain control, security, and cost-efficiency. Honestly, it’s a bit of a balancing act, but the kind that could pay off.
Navigating the Data Deluge: A Unified Approach
If you’re wondering just how messy the data landscape really is, consider this: according to Hitachi Vantara’s own State of Data Infrastructure Report, 98% of organizations use more than one type of storage platform. Even more striking, 57% are using all four. That’s a lot of data, living in a lot of places.
This scattershot setup makes it incredibly difficult to prepare data for AI. You end up with silos, inconsistent formats, and major delays. The EverFlex AI Data Hub addresses this head-on. It emphasizes data quality and governance—two things that often feel like afterthoughts but are absolutely crucial.
By consolidating data into a single, unified view, the platform feeds AI and BI tools with reliable, timely data. That alone can speed up insights and lead to better decisions. Jeb Horton, senior vice president of Global Services at Hitachi Vantara, summed it up well: the platform helps organizations “integrate, prepare and gain more control over relevant data despite the ensuing boom of unstructured data created by AI.” He also pointed out that it “empowers organizations to meet their data where it is,” which, if you’ve dealt with data sprawl, hits home.
Built for Performance: Under the Hood of the AI Data Hub
At the core of this service is the Virtual Storage Platform One (VSP One), and that’s more than just branding. It’s a serious piece of infrastructure that focuses on data completeness, accuracy, and compliance. The real magic lies in its ability to integrate data in real-time—without duplication. That alone helps maintain data integrity from the get-go.
The platform tackles not just technical bottlenecks but also cost-related pain points. It makes it easier to deploy AI and machine learning models faster, speeding up data pipelines and giving teams a common platform for everything from basic BI to more complex AI operations.
Several technologies are baked into this service:
- Unified Data Management: VSP 360 supports various storage types—block, file, object, and software-defined. It manages compliance, automates services, and even brings predictive insights via AIOps.
- Comprehensive AI Infrastructure: Hitachi iQ bundles GPU servers, fast storage, and networking, all while keeping governance and security in mind. It’s built to scale, without losing the plot.
- Modern Lakehouse Management: With Zetaris software onboard, the system connects to different data sources in real-time. It performs federated analytics where the data lives, which helps cut down on duplication and enhances data quality from the source.
There’s no question we’re on the edge of an AI boom. But the truth is, all the algorithms and models in the world mean little without solid data prep. That’s where this offering from Hitachi Vantara might find its real staying power.
By giving businesses a way to simplify and unify their sprawling data ecosystems—without sacrificing governance, cost control, or security—the EverFlex AI Data Hub could become a critical piece in the AI success puzzle. It’s not a silver bullet, sure. But it does seem like a genuinely thoughtful solution for a very real, very messy problem.
In the end, it might just help companies stop spinning their wheels and finally move forward into the kind of AI future they’ve been promised all along.
