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| 035 | _a.b12479408 | ||
| 099 | 9 | _aAIT ISPR DSAI no.25-01 | |
| 100 | 1 | _aPyae Sone Kyaw | |
| 245 | 1 | 0 |
_aFloware BP-floware data batchprocessing : _bsetting up cloud data batch processing infrastructure using microsoft Azure batch |
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_aPathum Thani, Thailand : _bAsian Institute of Technology, _c2025 |
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_a47 leaves : _bill.+ _e1 online resource |
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| 490 | 1 |
_aInternship Report ; _vno. DSAI-25-01 |
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| 500 | _aAn internship report submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Data Science and Artificial Intelligence | ||
| 502 | _aInternship Report (M. Eng.) - Asian Institute of Technology, 2025 | ||
| 520 | _aThis 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{u2019}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{u2019}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. | ||
| 650 | 0 | _aMicrosoft Azure (Computing platform) | |
| 650 | 0 | _aComputer communication systems | |
| 650 | 0 | _aDatabase management | |
| 700 | 0 |
_aChaklam Silpasuwanchai, _eChairperson |
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| 700 | 0 |
_aChantri Polprasert, _eExamination Committee |
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| 710 | 2 |
_aAIT Scholarships, _eScholarship Donor |
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| 810 | 2 |
_aAsian Institute of Technology. _tInternship Report ; _vno. DSAI-25-01 |
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| 856 | 4 | 0 |
_3Full-Text _uhttp://203.159.5.9/ait-thesis/detail.php?q=B23656 |
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_aBarcode : - _bCREATED : 2026-02-24 _cRECORD # : i13576380 _dLPATRON : 0 _eLCHKIN : - _f# RENEWALS : 0 _g# OVERDUE : 0 _hIUSE3 : 0 _iTOT CHKOUT : 0 _jTOT RENEW : 0 |
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