The modern factory's relationship with data is undergoing a significant change, shifting from a focus on the past to a future-driven approach. This requires an update in technology, particularly in legacy data historians that lack the necessary tools and interoperability for deriving meaningful insights. Successful predictive maintenance strategies and impactful data-driven decisions rely on real-time data processing at nanosecond precision, enabling advanced statistical analysis, machine learning models, and AI-derived insight. Amazon Web Services (AWS) and InfluxDB offer a suite of tools to modernize the Industrial IoT (IIoT) environment, including Telegraf for collecting industrial sensor data and InfluxDB for storing, visualizing, and analyzing large datasets. The integration of AWS Greengrass with InfluxDB enables real-time data processing and analytics, while Edge Data Replication (EDR) allows operators to collect, visualize, manage, and store data on their own terms. This technology enables users to connect to virtually any data source, process, analyze that data, and create visualizations to derive better decision-making and improved outcomes.