In an increasingly challenging oil and gas industry, a reliable and continuous well production test data acquisition system in real-time is crucial for achieving an intelligent field management. This study resulted in the development of a robust data flow architecture which integrates Data Management, Industrial Internet of Things (IIoT) and User Experience/User Interface (UX/UI) with the aim of automatizing production testing with multiphase flow meters (MPFM). The implemented data analytics platform ensures better production data quality, availability, reliability, and integrity. Key findings show that a layered architecture of data helps obtain an adequate benefit-cost ratio when using Azure services, that the understanding of the different communication architectures of the well test devices is important to integrate data properly, and that the data historization is relevant to avoid gaps due to transferring interruptions. Some of the proven benefits of this implementation include better asset management, enhanced production efficiency, carbon footprint reduction, cost savings and improved safety. The application scenario for which this real-time data automatization has been developed could also be potentially used to derive real case studies for Big Data technologies in other industries.