BIG DATA MANAGEMENT AND ANALYSIS

Course Description

This course provides a comprehensive definition of “Big Data” and the machine learning approaches for managing and processing them. With storage and computational power getting significantly cheaper and faster, big data sets are increasingly available and the need for machine learning approaches for handling big data becomes more significant. In this course, big data harvesting and manipulating methods, supervised and unsupervised machine learning techniques (especially artificial neural network), text data analysis and cloud computing are covered. By completion of this course, students will gain the ability to harvest big data from the web and process them by using supervised and unsupervised neural networks.

BIG DATA MANAGEMENT AND ANALYSIS

Evaluation Tools (Active Term)

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Course outcomes

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Course Syllabus

Reference Books & Course Materials

1. 01 Office 2013 Türkçe, Bayram Yıldız, 1.Baskı, ISBN:9786055201203
2. 02 Adım Adım Microsoft Office Professional 2010, Curtis Frye, Joyce Cox, Joan Lambert, ISBN:9789755096971

Learning Outcomes

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Program Outcomes

1. Demonstrate advanced knowledge of core concepts and theoretical frameworks in Management Information Systems, and apply them to develop innovative models that reflect current advancements in the field.
2. Analyze complex organizational problems and design integrated information systems solutions by applying advanced MIS knowledge and synthesizing multiple theoretical perspectives.
3. Develop and manage database systems and data-driven applications that ensure effective storage, retrieval, and use of organizational data in real-world contexts.
4. Utilize data analytics, business intelligence tools, and data visualization techniques to extract actionable insights and support strategic, data-driven decision-making.
5. Evaluate and apply emerging technologies such as AI, IoT, and Blockchain to drive digital transformation, enhance organizational performance, and formulate original research inquiries.
6. Conduct independent and collaborative research using appropriate methodologies, and communicate findings effectively through scholarly writing and presentations suited to diverse audiences.
7. dentify and address ethical, legal, and societal implications in the research, development, and use of information technologies, adhering to scientific and professional standards.
8. Collaborate effectively in multidisciplinary teams and demonstrate leadership in addressing complex technology-driven challenges.
9. Apply project management methodologies and tools to plan, execute, and monitor IT projects within organizational settings.
10. Develop and integrate information systems that align with organizational goals and strategies, supporting innovation and sustainable growth.
11. Perform comprehensive systems analysis and design, including requirements gathering, modeling, prototyping, and evaluating enterprise system architectures such as ERP, CRM, and SCM.
12. Assess and mitigate organizational information security risks by applying appropriate principles, technologies, and best practices in cybersecurity.

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