Imagine reaching the top of a climbing wall, feeling the thrill of success, and leaning back to lower down, only to look down and realize no rope is attached.
That horrifying moment actually happened to Bente Lønnquist Busch, Head of Data & AI Platforms at Telenor Norway.
While she climbed down safely that day, the incident left a lasting impression. Years later, Busch uses that terrifying story as a metaphor for modern enterprise data management: Are organizations building platforms that provide a safe, seamless auto belay, or are they handing teams a pile of gear and forcing them to figure out safety on their own?
In this presentation at the Data 2030 Summit, Busch unpacks why enterprise organizations must shift away from the traditional “infrastructure” mindset and start treating data platforms as real, evolving products.
The Evolution: Agile, DevOps, Data Mesh, and Platforms
To understand where data platforms are heading, Busch traces the evolution of digital operations over the last two decades:
- Software & Agile (2001+): software development shifted from slow, process-heavy waterfall methods to short cycles focused on user value.
- Infrastructure & DevOps (2008+): Continuous delivery led to merging operations and development, giving rise to application platforms focused on developer experience.
- Data Products & Data Mesh (2019+): Popularized by Zhamak Dehghani, data began to be treated as a valuable business product.
- Data Platforms (Today): Data platforms historically lagged behind, sitting in static data warehouses. Now, rapid advancements in AI demand that data platforms adopt the same product agility.
The Infrastructure Trap vs. The Product Mindset
Many data platforms trace their roots back to static legacy data warehouses. Built around ticket queues, rigid project funding, and outsourced maintenance, this model creates friction. When business units need something new, endless business cases delaying execution become the norm. 
In the era of rapid AI adoption, this legacy model can fail. To handle an unpredictable, high-speed future, platforms need built-in agility. Busch outlines a fundamental shift:
- Allocated, Continuous Funding: Instead of endless business cases for every tweak, funding long-term, cross-functional internal teams allows for continuous development and maintenance.
- Direct User Engagement: Moving away from cold, ticket-closing metrics toward active user engagement, internal community spaces, and measuring success by business value generated.
- Developer Experience & Self-Service: Just like an indoor climbing gym makes safety and access straightforward, a great data platform handles generic technical complexities behind the scenes so teams can focus on creating value.
- Opinionated Prioritization: User needs drive the roadmap, avoiding vendor-driven bloat or random managerial requests.
Real-World Execution: Lessons from Telenor Norway
How does a 170-year-old telecom company reshape its data strategy to avoid becoming a commodity provider? Busch shares practical details from Telenor’s ongoing transformation, including:
- Moving 80% of the organization into cross-functional “value streams.”
- Managing the transition from legacy architecture toward two future-ready platforms: one cloud-based and one tailored for strictly regulated telecom data.
- Unconventional organizational choices, such as bringing product designers into platform engineering teams to craft seamless user experiences.
Hear the Full Story & Join the Next Summit
Busch’s presentation blends relatable storytelling with actionable insights on modernizing enterprise data estates. To get the full breakdown including her deep dive into team ratios, DevOps integration for data, and platform governance, watching the complete recorded session is essential.
The Data 2030 Summit brings together top data leaders, CDOs, and enterprise architects from around the globe to discuss data platforms, governance, AI readiness, and operationalizing value.
Watch the full session online to dive deeper into this platform product framework.
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