AI is powered by volumes of data that must be stored effectively and efficiently to allow data access and at-scale AI deployments. Here’s what you need to know.
I’ve always rooted for the underdog. Maybe it’s the satisfaction of winning against all odds. Or it’s just mad respect for the struggle, passion, and tenacity that underdogs often exhibit in the face of significant obstacles. Like the real-life story of Billy Beane in the movie Moneyball. As the general manager of the Oakland Athletics, Beane used data and analytics to find undervalued baseball players on a shoestring budget. In 2002, his data-driven baseball team achieved a 20-game winning streak and the American League West title, competing against franchises spending over twice as much recruiting players.
Beane was ahead of his time, leveraging data to improve outcomes twenty-plus years before the concept was commonplace. Today, data-driven insights are universally embraced as the way to find smarter, more efficient approaches, and it works across industries and company sizes. Artificial intelligence (AI) is the analytics vehicle that extracts data’s tremendous value and translates it into actionable, usable insights.
In my role at Dell Technologies, I strive to help organizations advance the use of data, especially unstructured data, by democratizing the at-scale deployment of artificial intelligence (AI). The right technology infrastructure makes that possible. And it’s the silent but powerful enabler—storage—that’s now taking the starring role. Storage is the key to enabling and democratizing AI, regardless of business size, location, or industry.
Grappling with Data Access
As I talk with customers and organizations around the world, one trend is clear: issues with data access and data storage are escalating, creating business obstacles, and stalling progress. That’s because data is rapidly growing in volume and complexity, making data storage and accessibility both vital and expensive. Data accessibility is further exacerbated by the eruption and potential of unstructured data. Its sheer volume can overwhelm Fortune 100 organizations, medium-sized organizations, or start-up companies, yet unstructured data holds the key to breakthrough innovations. Thus, organizations need to solve data access and storage challenges.
The value of data and its actionable insights is skyrocketing with artificial intelligence (AI) capabilities because it’s viewed as the pathway to achieving competitive differentiation and accelerating business outcomes. To capture this value, AI implementations are going mainstream as organizations transition from research-based pilot programs to full-scale operational deployments. AI transitions highlight the organizational, “last mile” challenge of data access (where “last mile” means the data is there, but people cannot use it), which in turn stalls AI progress, and mandates that organizations rethink their data storage strategy.
Rethinking Data Storage
Many organizations have looked to the cloud to handle most of their data storage needs. However, a cloud-first storage approach is unsuitable for growing volumes of data because more data means more data movement. This incurs additional costs from ingress and egress fees and increases data latency, making cloud-first storage approaches ineffective for AI implementations at scale.
Instead, organizations need newer storage models designed to handle modern workloads in near real-time. Storage platforms must be easy-to-integrate, scalable, and validated for managing unstructured data, combining functionality such as a file system, volume manager, and data protection. The ideal platform must address the major challenges of unstructured data by:
Providing accessible, findable data, quickly and accurately
Storing massive amounts of data in a cost-effective manner
Protecting files and data as they move around and change over time
By successfully meeting these needs, Dell Technologies helped one organization score a “technology touchdown” in Miami, Florida.
Improving Experience at Hard Rock Stadium
Few environments need to scale unstructured data securely and on-demand like live sporting events. Fluctuations in the size of the fan base, video footage, and other variables introduce unique challenges. Dell ECS and Dell PowerScale are designed and tested to meet these types of on-demand challenges.
Just ask the Hard Rock Stadium, in Miami, Florida, which uses the highly flexible, secure PowerScale platform to improve fan experiences. It does this for events and crowds of all sizes, such as Miami Dolphin games, Formula 1 Miami Grand Prix, Miami Open Tennis Tournament, international soccer, and even the Super Bowl LIV to meet a wide array of contactless fan needs, improving outcomes for fans, franchises/organizations, and event teams. View the Hard Rock Stadium 2-minute video here.
The right storage can do that and more for organizations that want to leverage unstructured data via AI at scale. The benefits of doing so can be significant while, on the contrary, doing nothing can hold steep, indelible consequences.
Elevating the Role of Storage
I think Billy Beane, who still supports the Oakland Athletics team today, would appreciate this sports-based customer story. It’s built on his premise of getting ahead by using the power of data–unleashed by AI and enabled by a flexible, scalable storage platform.
Data’s last-mile challenge squanders the investment of capturing and storing data at the most costly and inopportune time. Newer storage models can mitigate this opportunity cost. That’s what I help organizations around the world accomplish. My goal is to help democratize the use of AI and build a stronger future, company by company, and for underdogs and leaders alike.
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Read my related article about data management here.
In a world of unstructured and often untapped data, Dell Technologies storage solutions such as ECS and PowerScale, can help power your AI journey. Learn more here.
Dell Technologies works together with Intel to help organizations modernize infrastructure and leverage the power of data and AI. Modernizing infrastructure starts with creating a more agile and scalable data architecture with the flexibility to support near real-time analytics. Analytic workloads now rely on newer storage models that are more open, integrated, and secure by design to help organizations unlock and use the full and tremendous potential of their data. Learn more here.
Powering business with data means making the data easier to manage, process and analyze as part of a data pipeline, so infrastructure can meet the data wherever it is. Intel helps customers build a modern data pipeline that can collect, extract, and store any type of data for advanced analytics or visualization.
Learn more here.
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