Title page for etd-0624115-131244


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URN etd-0624115-131244
Author Shun-hsien Chuang
Author's Email Address No Public.
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Department Computer Science and Engineering
Year 2014
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title The study of a big data platform for mining computation and storage : the case study of national health insurance database
Date of Defense 2015-07-17
Page Count 68
Keyword
  • Impala
  • Big Data Computing
  • Apache Hadoop
  • Hive on Spark
  • Apache Hive
  • National Health Insurance Research Database
  • Abstract Our country has a complete national health insurance. The treatment records of patients are recorded into the National Health Insurance Research Database. With the treatment records of patients, we can use big data technology to analyze the treatment records of patients and to get useful information. This useful information is currently used in the preventive healthcare or improves the effectiveness of treatment and medication. We hope these researchs can help reduce the cost of nationl health insurance or enhance the effectiveness and quality of health care, even we can prevent diseases. However, these massive health insurance data are not suitable for usual data processing software. We must import a new approach to solve these massive health insurance data.
    In this paper, health insurance data are stored into the big data computing platform, then, we use a vatiety of analysis tools for accelerating data analysis. The purpose of this paper is discussing which analysis tool is suitable for the usual research topic of medical staffs. We will use several typical computations to analyze the performance of data computing and storing.
    Keywords: National Health Insurance Research Database, Big Data Computing, Apache Hadoop, Apache Hive, Hive on Spark, Impala
    Advisory Committee
  • Shihn-Sheng Wu - chair
  • Yen-Hsia Wen - co-chair
  • Jui-Hsiu Tsai - co-chair
  • Shi-Huang Chen - co-chair
  • Chun-Hung Lin - advisor
  • Files
  • etd-0624115-131244.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2015-08-03

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