Predictive analytics is a powerful tool that uses statistical models and machine learning algorithms to identify trends based on historical and real-time data. It can be used in various applications such as supply chain management, equipment effectiveness, anomaly detection, etc. The key to harnessing the power of predictive analytics lies in collecting consistent, reliable time series data. Time series databases are optimized for storing and managing this type of data, while data lakes offer a cost-effective long-term storage solution. Combining these technologies allows organizations to leverage the benefits of both data collection methods to generate deeper insights. By using a time series database and data lake together, businesses gain the necessary storage infrastructure for effective predictive analytics, machine learning, and statistical models.