With the 2026 Winter Olympics about to kick off in Italy, people’s minds have naturally turned to the topic of competitions, teams, and medal counts. There is an infectious culture of excellence that surrounds the Olympics that always catches the whole world by surprise.
It’s worth reflecting on where that culture comes from, and what goes into making it. We all know that there is a lot more to winning at the Olympics than each individual athlete alone. First, many sports rely on teams, but beyond that, an army of coaches, analysts, and nutritionists helps make each win a win.
Cultures of excellence in the Olympics and data
This culture of excellence is worth reflecting on because it isn’t confined to the Olympics alone; in fact, many areas of life also include similar support structures aimed at achieving mission-critical results.
For example, closer to home, the data world rests on similar principles, and it’s worth using the lens of the Olympics to reflect on what nurtures and engenders success in any area, even data.
Accordingly, in the spirit of the games, I’d like to look at the hidden support behind every Olympic win and consider it alongside your data strategy.
On your mark, set, go.
Silos vs. Teams
First, let’s talk about teamwork. Some sports require teamwork to get started, but beyond that, every sport requires a team behind the scenes as well. To succeed, these teams need not only to be in proximity to each other; they also need to work towards a shared vision. More than that, they need to inch towards success, one milestone at a time.
Think of what every Olympian says when they win–the win was not won in the moment it was realized; rather, it was won at each mile leading up to it. Every training session, every iteration of success led to the final moment of completion and success. At the end, whether bronze, silver, or gold, the moment of the win is merely the most emblematic pinnacle of success, built atop a large pyramid of effort. To get there, teams need to come together in a shared vision and sustain that effort over time, against all obstacles.
Data teamwork
This is exactly what data teams do, too. The stakes may be different–and may involve data architecture more than they do sub-second training metrics–but the same spirit of teamwork is also required for success in data engineering. Here too, it is not enough for teams to simply be placed next to one another and then hope for success. In the data world, that merely creates data silos. Instead, they need to share a vision of shared commonality that breaks down silos and pushes, mile after mile, towards a common goal.
Many individuals, one goal
It’s worth reflecting on what this approach means for individuals. Just like the Olympics, data teams are made up of multiple players. You can think of this as similar to positions in a sports team, and just like a team sport, the data engineers, data analysts, and business users each need to come together towards a common goal.
To do this, they need to understand not only the importance of their own position but also that of their team members. The data analyst end user relies on the data engineer to understand their needs upstream. Meanwhile, the data engineer needs to understand the business logic from the business user. Each of these positions works together to achieve success in every bit the same way that team members work together on a hockey team, a curling team, or any other team sport.
Agility and adaptability
The best laid plans are apt to change. Olympians train for the expected, but they also know to expect the unexpected. This is where training for resiliency and agility comes into play. In competition, the difference between success and failure can come down to the judgment inculcated during practice. Training, repeatedly, over and over again, not only prepares athletes for the standard case. It also creates resiliency.
Resilience is also a key virtue in data architecture. Like a competition, a data production environment is a living entity subject to expected norms of operation, but is often likely to deviate from them. This is when contingencies and planning enter the mix. Is your data architecture designed for the unexpected? Is it adaptable and able to operate outside the use cases you might anticipate? Over time, all competitions throw up unexpected challenges, and so too does every production environment face its own challenges.
The difference then, between success and failure, comes about when you consider what happens when the unexpected happens, and whether you’ve planned for it.
Starburst. Built on choice and teamwork
Starburst is built for real success in a changing, flexible world. It’s designed to access all your data, teams, and operations via a single foundation for all your data. To do this, we help teams work together to achieve their goals across organizations and data sources.
In this, we’re built around twin pillars of choice and change. Like the Olympian who trains for every condition, only to meet a new situation in the moment of competition, we’re built to adapt to plans that may not even have been put in place yet.
This Olympics, when you’re enjoying the outcomes of strong teams, unified visions, and hard work every step of the way, think of the other areas where similar approaches yield similar results.
