- Designed logical and physical databases (3NF) from scratch, considering business requirements for staging data and processed data for the web-app with triggers, stored procedures, and views.
- Created ETL scripts that run every day in batch processing to load data from the historian database to the in-house staging database.
- Developed a complex R Shiny web application for 8 plant units and its respected trains (Total: 8 Menu-Items and 56 Sub-Menu-Items) through shiny modules with various inputs to analyze time-series data.
- Deployed the app on RStudio Connect with load-balancing and user controls, but it could be installed and run locally through a docker container or deployed as an R package (golem philosophy) with minor patchwork.
- Provided a plant-wide web application to analyze various domain-specific tags and trends for chemical gasification processes in plant units using IoT sensors data for multi-level internal stakeholders from senior upper-level management.
- Allowed users to make smart decisions by ensuring the plant is running smoothly and minimizing downtimes.
- Reduced a significant amount of time of data preparation for manual reporting and sudden breakdown times.
- Modernized the Shiny app, reducing user wait time, ensuring reproducibility, and improving the app’s performance.
- Enabled the company to make data-driven decisions, thus improving operational efficiency and providing new insights.
- Upskilled the team in using advanced technologies for analysis and decision-making.