A free course to learn how to turn data, marketing, and technology into better decisions.
GinnyTech nasce per chi non vuole studiare strumenti isolati. Il punto è imparare come si collega una domanda di business a un sistema di misura, a un modello dati e a una scelta operativa.
- modules
- 21
- core lessons
- 236
- paywall
- 0€
from the method to the final capstone
with a clear study order
open training, separate services
The thesis
The market doesn’t reward those who only know tools. It rewards those who can turn data into decisions.
Per questo il corso tiene insieme analytics, marketing engineering e data engineering: nel lavoro reale una campagna genera dati, i dati entrano in una pipeline, una dashboard mostra un problema e qualcuno deve decidere.
Data
Measure before deciding
Tracking, KPIs, data quality, and dashboards serve to understand what’s happening, not to decorate reports.
Marketing
Connect numbers and growth
Funnels, campaigns, retention, LTV, and budget become readable when metrics are well built.
Technology
Build reliable systems
Pipelines, warehouses, real-time analytics, and AI agents are explained as parts of an operating system for decision-making.
Positioning
Not a generic course. A path to think better about work.
La differenza è nel filo logico: non parti dal software, parti dal problema. Gli strumenti entrano quando aiutano a misurare, verificare e comunicare una scelta.
Not like this
A list of tools to memorize.
Here instead
A method to move from question, measurement, and model to a decision.
Not like this
Marketing separated from analytics and technology.
Here instead
A unique path where campaign, tracking, pipeline, and dashboard talk to each other.
Not like this
Generic theory without operational context.
Here instead
Examples and cases designed for real work: budget, funnel, quality, and responsibility.
Study method
Each block must produce clarity, not just passive knowledge.
Start with the question
First comes the business problem: what you want to understand, which decision depends on the answer, and who will use it.
Design the measurement
Define events, KPIs, denominators, data quality, and checks before trusting a chart.
Build the system
Models, pipelines, and dashboards must make data reusable, verifiable, and readable by the team.
Close with a choice
The output is not “an insight”: it’s a clear recommendation, with limits, trade-offs, and next action.
Who it's useful for
It’s for those who need to connect learning, role, and real decisions.
La pagina non prova a parlare a tutti: è pensata per chi vuole usare i dati come disciplina operativa, che stia iniziando o che debba rimettere ordine in un team.
Students and juniors
You need practical basics, not just definitions.
Build an ordered path and portfolio materials.
Marketer
You want to better understand campaigns, funnels, and conversions.
You learn to use metrics and dashboards to choose the next action.
Analyst
You know how to work with data but want to better understand the business context.
You connect analysis, stakeholders, decision memos, and economic impact.
Founder and team
You need to bring order to tracking, KPIs, and reporting.
You gain a common language between marketing, product, and technology.
Why it’s free
The barrier shouldn’t be the paywall.
Il corso è gratuito per ridurre la distanza tra curiosità e competenza reale. Chi studia deve poter vedere un percorso serio prima di comprare consulenza, tool o formazione avanzata.
Clear boundary
Open training, separate project work.
Le lezioni costruiscono cultura e basi solide. Le consulenze restano un servizio distinto, utile quando serve applicare il metodo a un sistema reale, con vincoli, dati e priorità già presenti.
Next step
If you want to learn from real work, start with the path map.
Segui l’ordine consigliato se parti da zero. Apri il catalogo se sai già dove vuoi entrare. Prenota una call solo quando hai un progetto concreto da chiarire.