Publications

The objective of this paper is to introduce the development and implementation of Processing Integrated Transformation Analytics (PITA), a comprehensive data management and machine learning platform designed to address complex multi-domain data integration challenges in multiple departments. The platform specifically focuses on the integration of diverse data sources, including IoT sensors, geospatial, geoscience data, and production reports within Saka Energi Indonesia’s operational framework. PITA uses a hybrid architecture that combines Python scripting with open-source applications to enable automated data collection, transformation, and distribution in both real-time and scheduled scenarios. The platform successfully manages data from six production fields, processes information from over 900 surface facility sensors, and has converted over 100 2D seismic lines into standardized geospatial formats. Data sources are consolidated from multiple formats, including Excel spreadsheets, API services, field sensors, and email communications, into dedicated SQL databases. The deployment has enhanced data processing efficiency and given many departments data access. This study emphasizes the technical architecture and quantitative benefits of the PITA platform, thereby emphasizing its role in advancing enterprise digitalization through open-source technologies.