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  <titleInfo>
    <title>Floware BP-floware data batchprocessing</title>
    <subTitle>setting up cloud data batch processing infrastructure using microsoft Azure batch</subTitle>
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  <name type="personal">
    <namePart>Pyae Sone Kyaw</namePart>
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    <namePart>Chaklam Silpasuwanchai</namePart>
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  <name type="personal">
    <namePart>Chantri Polprasert</namePart>
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    <namePart>AIT Scholarships</namePart>
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    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>2025</dateIssued>
    <issuance>monographic</issuance>
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  <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{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.</abstract>
  <note>An internship report submitted in partial fulfillment of the requirements for the degree of  Master of Engineering in Data Science and Artificial Intelligence </note>
  <note>Internship Report (M. Eng.) - Asian Institute of Technology, 2025</note>
  <subject authority="lcsh">
    <topic>Microsoft Azure (Computing platform)</topic>
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  <subject authority="lcsh">
    <topic>Computer communication systems</topic>
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    <topic>Database management</topic>
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      <title>Internship Report ; no. DSAI-25-01</title>
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