A data vision is not a technology roadmap. This distinction matters more than almost anything else in this module.
Companies routinely confuse "We will build a Data lakeData lakeA data lake is a centralized repository that stores large volumes of raw data in its native format, from structured tables to unstructured files, until needed.View full definition →" with having a data strategy. A Data lakeData lakeA data lake is a centralized repository that stores large volumes of raw data in its native format, from structured tables to unstructured files, until needed.View full definition → is an infrastructure choice. A data vision answers: "What kind of company do we want to become through data?"
Netflix's data vision isn't "We will build recommendation algorithms." It's "We will give every subscriber the feeling that Netflix was built just for them." The algorithms are the how. The vision is the why and what.
The north star metric is a single, measurable expression of your data vision. It should:
Netflix: "Hours of joy per subscriber per month." Every data initiative is evaluated by whether it moves this number. Their recommendation engine accounts for approximately 80% of content watched. The engine exists to serve the north star.
Spotify: "Daily active listening time per user." Their Discover Weekly feature, a personalized playlist for 600M+ users every Monday, exists to move this number. Behind it: data infrastructure processing 4 billion events per hour.
Michelin: A more surprising example. The tire company that launched the Michelin Guide to sell tires eventually realized the mapmapUsing software to automate repetitive marketing tasks and campaigns, enabling personalisation at scale across channels like email, web, and social.View full definition → and navigation data assets they'd built over decades had independent commercial value. The Michelin Maps product (ViaMichelin), data partnerships with automotive OEMs, and their work with HERE Technologies are all expressions of a data vision that goes far beyond selling tires.
Knowledge check
1. According to the lesson, what is Netflix's data vision?
2. What percentage of content watched on Netflix is driven by their recommendation engine, according to the lesson?
3. The Michelin example illustrates which broader principle about data vision?
4. Select ALL the criteria that a north star metric should meet according to the lesson:
Sélectionnez toutes les réponses correctes.
5. Select ALL statements that correctly distinguish a data vision from a technology roadmap:
Sélectionnez toutes les réponses correctes.
Why, What business problem does data fundamentally solve for you? Not "we have lots of data" but "we have specific strategic challenges that data is uniquely positioned to solve." The CDO who can't answer the "why" in 30 seconds doesn't have a vision, they have a technology roadmap.
What, What data-drivendata-drivenAn approach where decisions are systematically informed by data analysis rather than intuition alone.View full definition → capabilities will distinguish your organization from competitors? What will you be able to do in three years that you can't do today? Test: if a competitor could replicate your capability in six months, it's not a strategic vision.
How, What architecture, talent, and governance infrastructure will support this vision? This is where technology choices live, and only here. The vision drives the architecture, not the reverse.
When, What does 18-month success look like? What does three years look like? A vision without a timeline is a dream. A timeline without a vision is a project plan.
Amazon's Data flywheel is the clearest articulation of a data vision creating competitive moatmoatA lasting edge over competitors: a resource, capability or position they cannot easily replicate, letting a firm earn above-average returns over time.View full definition →:
More customers → More data → Better recommendations → Better customer experience → More customers
Every data initiative Amazon runs, recommendation engines, Alexa, Amazon Go's cashierless stores, their supply chain AI, serves this flywheel. Their CDO structure exists to accelerate the cycle and prevent data from escaping into Data silos.
The result: their recommendation engine drives an estimated 35% of total revenue. Their advertising business, built entirely on First-party dataFirst-party dataData collected directly from your own customers and prospects through your own channels: your most reliable and privacy-compliant source.View full definition → that no competitor can match, generates $47B+ annually, making Amazon the third-largest digital advertising business in the world, despite not being primarily an advertising company.
This is what a data vision looks like when it's working.