Stream Smarter, Not Harder: A Data-Driven Solution based on Recommendation Systems for Streaming Platforms through Power BI

Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsStreaming video platforms have gained remarkable popularity in recent years, offering users affordable access to a vast variety of entertainment content. Platforms such as Netflix and Spotify have fundamentally transformed the consumption of digital content, from films and TV programmes to music and podcasts, allowing instant access without the need for lengthy downloads, often through a simple subscription fee or freemium model. This revolution has reshaped the entertainment industry, establishing a dynamic global distribution channel that quickly connected creators to a massive audience. Nevertheless, the abundance of competitors and a large volume of content competing for viewers' attention has forced industry leaders to re-evaluate their content recommendation strategies. To battle for their market share in this competitive environment, these industry giants must leverage the power of data-driven insights through Artificial Intelligence and Machine Learning in order to select appealing content recommendations and ultimately foster deeper engagement. Therefore, the goal of this project was to create a complete Business Intelligence solution using the data of four streaming platforms and deliver an effective content-based recommendation system to boost audience level. Therefore, aimed of achieving this objective, a recommendation algorithm was applied to the different datasets and eight dashboards were created to display powerful insights of the four most popular streaming platforms worldwide