Measure TV viewership: Minimum Viable Product - GVC

Data analysis
Client
Hybrid Company
Project type
Data analysis
Project year
2020
Project tech
Python, Jupyter Notebooks, MongoDB, InfluxDB, Snowflake Data Cloud

Improving Evaluation of TV Viewership through MediaTech in collaboration with Hybrid Company

During two weeks I worked on the creation and validation of an MVP while building bonds with peers from across the world, working professionals at Fortune 500, and investors from the Silicon Valley. As a team technical lead, I:

- Extracted, transformed, and loaded raw data (ETL) from three connectors to a cloud database.

- Created algorithms to help analyze and predict the amount of traffic (TV viewership) on a specific period.

- Implemented a machine learning algorithm for anomaly detection.

- Communicated the work status to the project owners and kept track of tasks and progress of the team.

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We learned that we were selected for the sprint basically on New Year's Eve. Then many students started applying and I was very surprised how handy they were, they worked really brilliantly. Officially, I was a mentor, but I must add that I was helped by some great colleagues who are technically proficient. It was a great experience both managerially and organizationally, a week and two weekends of the American sprint, which was fast and wild, over four time zones, and we made it. I'm really proud of my team.

Lukas Hnilicka, CEO & Chairman of Hybrid Company

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