Alternative data refers to non-traditional data sources that provide insights into financial instruments, complementing conventional sources like SEC filings and media reports. This data, generated by individuals, companies, and IoT devices, includes unstructured social media interactions, structured transactional data, and sensor-generated geolocation information. Investment firms are increasingly utilizing alternative data to gain a competitive edge, with early adopters like hedge funds and private equity managers leading the charge. As global data generation is expected to reach massive levels by 2025, the integration of AI and machine learning tools is crucial for analyzing these large datasets. Alternative data is becoming pivotal in model-driven investing, helping firms identify innovative strategies for generating alpha, especially in the wake of the digital shift accelerated by COVID-19. The data can be sourced through web crawling or purchased from third-party vendors, and its applications range from predicting market movements to assessing risk based on geospatial data. As the adoption of alternative data becomes more widespread, its potential to transform investment strategies and decision-making processes grows, paving the way for sophisticated predictive models and revenue streams.