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Foundation of Big Data

KMUTNB
Enrollment is Closed

About This Course

The foundation of Big Data lies in understanding the principles of data storage and management. Efficient data storage structures are critical for handling the vast and varied datasets typical in Big Data environments. Data engineering is pivotal in preparing, processing, and optimizing data flows to ensure accessibility and usability.

Key to Big Data is a firm grasp of database system concepts and architecture, which define how data is organized, stored, and retrieved efficiently. Information modeling facilitates the logical structuring of data, ensuring relevance and usability. Database design builds on this, focusing on creating systems tailored to specific use cases, often explored through practical case studies.

A cornerstone of database systems is relational algebra, which underpins the Structured Query Language (SQL). SQL enables powerful and precise data manipulation through query processing, which optimizes data retrieval.

Transaction management ensures consistency and reliability during concurrent data operations to maintain robust operations. Meanwhile, database integrity and security safeguard data accuracy and protect against unauthorized access. Finally, database management provides tools and processes to monitor, maintain, and enhance database performance, forming a comprehensive framework essential for the scalability and reliability of Big Data systems.

Requirements

070153602 Contemporary Programming Framework

Course Staff

Maleerat Maliyaem

Asst.Prof.Dr.Maleerat Maliyaem

Asst. Prof. Dr. Maleerat Maliyaem, a lecturer in the Department of Information Technology, has a robust academic background and expertise in various areas of computer and information sciences. Here's a summary of her profile:

Educational Background

  1. Doctorate:

    • Ph.D. in Information Technology (International Program)
    • Institution: King Mongkut's University of Technology North Bangkok
  2. Master's Degree:

    • M.Sc. in Computer and Information Technology
    • Institution: King Mongkut's University of Technology Thonburi
  3. Bachelor's Degree:

    • B.Sc. in Computer Technology
    • Institution: King Mongkut's Institute of Technology North Bangkok

Subjects Taught

  1. Information Retrieval Systems:

    • Techniques for efficiently retrieving relevant information from large datasets or repositories.
  2. Decision Support Systems:

    • Systems aimed at aiding decision-making processes through data analysis, modeling, and prediction.
  3. Natural Language Processing:

    • Computational techniques for processing and understanding human language.
  4. Machine Learning:

    • Training algorithms to identify patterns and make decisions from data.
  5. Data Mining:

    • Extracting meaningful insights and knowledge from vast datasets.

Her teaching portfolio indicates a strong focus on theoretical and applied computational fields, highlighting her contribution to the advancement of these disciplines through both education and research.

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