Floware BP-floware data batchprocessing : setting up cloud data batch processing infrastructure using microsoft Azure batch | |
| Author | Pyae Sone Kyaw |
| Call Number | AIT ISPR DSAI no.25-01 |
| Subject(s) | Microsoft Azure (Computing platform) Computer communication systems Database management |
| Note | An internship report submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Data Science and Artificial Intelligence |
| Publisher | Asian Institute of Technology |
| Abstract | This 6-month internship report highlights the successful implementation of an automated cloud data engineering pipeline at Floware, a startup specializing in mobility flow analysis. The primary objective focused on designing and deploying an Azure Batch Processing solution to streamline the company’s data processing workflows.Commencing in September 2024 and concluding in March 2025, the internship centered on transforming manual data processing tasks into an automated, scalable cloud solution.The implementation involved creating containerized environments using Docker, establish ing efficient data flows between Azure services (Batch, Container Registry, Blob Storage), and developing standardized processing workflows for both computer vision and Bluetooth sensor data. Beyond the primary cloud engineering focus, serving as the company’s sole data scientist necessitated fulfilling various critical responsibilities, including data engineering, analysis, and visualization for client needs. Complex data transformation tasks were successfully automated, from processing raw sensor data to generating actionable insights such as Origin-Destination matrices and other related trajectory,Speed and Frequentation analyses from Bluetooth and Computer Vision Data . The outcomes demonstrated significant improvements in processing efficiency, with automated batch processing reducing manual intervention while ensuring consistent, reliable and efficient results. Additional achievements included developing visualization solutions using PowerBI, contributing to physical sensor deployment operations, and providing data-driven solutions for specific client requirements. This internship fostered valuable experiences in cloud engineering, data science, and startup operations, contributing to a deeper understanding of implementing scalable data solutions in real-world applications. |
| Year | 2025 |
| Type | Internship Report |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Data Science and Artificial Intelligence (DSAI) |
| Chairperson(s) | Chaklam Silpasuwanchai |
| Examination Committee(s) | Chantri Polprasert; |
| Scholarship Donor(s) | AIT Scholarships |
| Degree | Internship Report (M. Eng.) - Asian Institute of Technology, 2025 |