Back in 2010, I introduced my employer to the five Vs of big data: Volume, Velocity, Variety, Veracity, and Value. At that time, the concept was gaining traction as businesses grappled with the explosion of digital information. Nearly 15 years later, the five Vs remain highly relevant for Artificial Intelligence.
The tech world has come a long way, but the core ideas behind the five Vs are more crucial than ever and a solid foundation for tackling the challenges of AI in our data-driven world. Let's dive in and see why each V still matters today.
Volume: Fueling the AI Engine
In 2010, data professionals were beginning to grasp the sheer magnitude of big data. Today, AI thrives on this explosion of data, particularly for training machine learning models. The availability of massive datasets determines an AI model's ability to generalize and perform effectively.
But with great volume comes great responsibility. An enormous amount of data is generated daily, presenting organizational challenges in handling one of their most important assets. Companies must be concerned with responsibly storing, processing, securing, and ensuring the highest ethical standards when using data—ensuring that their AI initiatives are both sustainable and impactful.
Velocity: The Need for Speed
Data velocity has always been a challenge, but it's a game-changer in AI. Real-time applications like fraud detection, personalized recommendations, and autonomous systems demand instantaneous insights. In 2010, the focus was on fast-moving data streams; today, we also discuss latency in AI decision-making.
AI needs to be as quick and flexible as the data it uses. It takes a solid infrastructure setup to keep up with fast-moving data and ensure real-time predictions stay spot-on.
Variety: Beyond Structured Data
Variety was once synonymous with handling structured and unstructured data. Today, AI extends this challenge by integrating diverse data types—text, images, audio, video, and beyond. Think of chatbots that understand text, voice assistants that interpret speech, or multimodal AI that combines vision and language.
Variety enriches AI's capabilities, making it more human-like and adaptable. But it also introduces data integration and harmonization complexities, demanding thoughtful preparation and governance.
Veracity: The Foundation of Trust
In 2010, veracity was all about ensuring data was clean and reliable. Now, in the age of AI, it's front and center when dealing with data biases, mistakes, and ethical issues. Bad or biased data can harm results and cause clients to lose trust in AI systems.
Value: The True Measure of AI's Success
When I first discussed the five Vs, value was all about turning data into useful insights. These days, it's a bigger deal. AI has to prove its worth by driving real business results—like boosting efficiency, cutting costs, and helping make smarter decisions.
Value isn't just about business—it's about making a difference in society. Whether it's in healthcare or education, AI has the power to tackle significant global issues. But to really unlock that potential, organizations need to make sure their AI projects align with their goals and actually contribute to something meaningful.
Why the Five Vs Matter More Than Ever
Looking back at my 2010 presentation, I'm amazed at how these five principles are still relevant and vital, especially with all the challenges AI brings today. As more organizations embrace AI, the five Vs offer a simple, timeless guide to getting it right:
Volume - ensures we have the data needed to fuel AI.
Velocity - drives real-time applications and responsiveness.
Variety - enables AI to handle the complexity of modern data.
Veracity - builds the trust necessary for risk mitigation and ethical implementations.
Value - keeps us focused on outcomes that matter.
These principles are more than technical details—they're a philosophy. Adapting the five Vs helps us create AI systems that are not only powerful but also responsible, scalable, and designed to benefit everyone.
Looking Ahead
As we step into an AI-driven future, the lessons we've learned continue to light the path. The five Vs remind us that AI isn't just a tool—it's the heartbeat of innovation. Whether it's 2010, 2025, or beyond, these principles keep showing us how to approach AI with care, creativity, and a focus on doing great things.
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JM Abrams
Chief Data Culturist
LF01
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