Data Director · Media & Entertainment
Data Director Training for Media & Entertainment
You already know how to run a data team. What you need here is the sector context that makes your decisions sharper: how audience measurement actually works across linear TV and streaming, what Nielsen, GRP or completion rates mean for your budget conversations, how GDPR and cookie deprecation reshape targeting on platforms like Disney+ or TF1, and where the ad tech stack sits between Amazon, Google and the broadcasters fighting for the same inventory. This is the foundation most data courses skip, and it's the one your board actually asks you about.
On top of that grounding, you get the full data curriculum: modeling, governance, ML fundamentals, applied through interactive case studies built around subscription churn, content recommendation and rights management. An action playbook gives you templates to bring back to your team this week. A sector-specific assessment tells you exactly where your gaps are compared to peers running data at Netflix, Canal+ or Warner Bros Discovery scale, so you stop guessing and start closing them.
31 lessons · ~6 h · resumes where you left off
Your program
A focused program built on your vertical's content: the sector first, then your discipline applied to it.
The generalist Data track
The full craft of the discipline, beyond your sector.
More resources
Interactive tools
Frequently asked questions
Who is this Data Director track for?
Data Director Training for Media & Entertainment is built for people who already lead a data team and now need the sector context: streaming, broadcast, content platforms and the ad tech that surrounds them. It assumes you know how to run modeling and governance work, so it spends its time on how audience measurement, rights and platform economics change your decisions. If you have never managed a data function, the general data curriculum is the better starting point.
What does this add compared to a generic data course?
The sector layer. Generic data programs teach modeling, governance and ML fundamentals but skip how audience measurement works across linear TV and streaming, what Nielsen, GRP or completion rates mean in a budget discussion, and how GDPR and cookie deprecation reshape targeting on platforms like Disney+ or TF1. That context is what a board asks a Data Director about, and it comes here alongside the full data curriculum rather than instead of it.
Is access free, and do I need an account?
Reading is free and open. An account is only there to keep track of where you stopped in the lessons and to store your assessment results. There is no paywall, no trial period and no upsell behind the content.
Does the program deliver a diploma or a recognized certification?
No. There is no diploma, no state-recognized certification and no affiliation with a school or university. What you get is the sector material, the case studies, the playbook templates and an assessment that positions your gaps.
What do the case studies actually cover?
Three situations that dominate data work in media: subscription churn, content recommendation and rights management. They are interactive, so you make the modeling and governance calls yourself rather than reading a finished answer. Each one applies the curriculum material instead of restating it.
How does the assessment tell me where my gaps are?
The assessment is sector-specific: it measures you against the level expected of people running data at the scale of Netflix, Canal+ or Warner Bros Discovery, not against a generic data baseline. The output points to the areas to close first, which is also how you decide which lessons to read in what order. Results are kept in your account so you can retake it later and compare.