Big Data Management
PİRİ REİS UNIVERSITY
FACULTY OF ECONOMIC AND ADMINISTRATIVE SCIENCES
|
Course Name : Big Data Analytics
|
Degree: Bachelor
|
|
Code
|
Year/Semester
|
Local Credits
|
ECTS Credits
|
Course Implementation, Hours/Week
|
|
Course
|
Tutorial
|
Laboratory
|
|
YBS 405
|
Fall
|
3
|
5
|
3
|
0
|
0
|
|
Department
|
MANAGEMENT INFORMATION SYSTEMS
|
|
Instructors
|
Assist. Prof. Masoud Shahmanzari
|
|
Contact Information
|
e-mail: TBA
|
|
Office Hours
|
Wednesday 13:00- 16:00
|
|
Web page
|
TBA
|
|
Course Type
|
|
Course Language
|
English
|
|
Course Prerequisites
|
-
|
|
Course Description
|
Theoretically and practically, it contains the basic conceptual components for understanding the principles of “Big Data” at the entry level and examining it in an interdisciplinary perspective.
|
|
Course Objectives
|
Students taking this course will focus on analyzing various applications that use big data systematically and analyzing related data analytics problems encountered in these applications. Students are also expected to practically activate low-level programming skills in scenarios with big data management dependencies, along with case studies. Python is the main programming language of the course.
|
|
Course Learning Outcomes
|
By students who passed from Big Data Analytics YBS 405 successfully
I. Know the principles of “Big Data” conceptually and discuss its importance in terms of academic and practical perspectives.
II. Gains analytical perspective on the management of applications with the “Big Data” approach and gains awareness of the technologies used.
III. You can make technical design practices at the entry level, use the related computing packages and objects, and gain a perspective on big data architecture within this scope.
IV. Can use Python for entry-level data management and analytical compilations and open source research and project initiatives accordingly.
|
|
Instructional Methods and Techniques
|
The presentation of theoretical and practical techniques. Students are expected to do exercises in online classes and a project
|
|
Tutorial Place
|
|
|
Co-term Condition
|
-
|
|
Textbook
|
Data Science and Big Data Analytics by EMC
|
|
Other References
|
Lecture notes, files and exercises.
|
|
Homework & Projects
|
Students will be required to solve problems presented in worksheets or online portal, to aid their efforts to follow the development of the course content and to prepare for the examinations.
|
|
Laboratory Work
|
-
|
|
Computer Use
|
Students will use computers during the online sessions
|
|
Other Activities
|
|
|
Other Conditions
|
In case of plagiarism and cheating, university legislation is applied. Assignments must be submitted on the delivery date in accordance with the announced format. Assignments after the deadline are not accepted. The student who does not take the exam must bring the doctor's report or inform the excuse by an e-mail. It is at the discretion of the instructor to make a make-up exam with the exception of the report status.
|
Success Requirements: Attendance is mandatory. Students must attend the course in accordance with the legislation, and if there is an excuse, they should report it at the appropriate time. One written midterm exam is given. 1 project assignments is given and expected to present them. These are all essential for the midterm grade. The percentage distributions is in the below table. The final term-end score is calculated by adding the final exam score.
Measurement and Evaluation Methods: The percentage distribution of related exams and projects are follows:
|
Assessment Criteria
|
Activities
|
Quantity
|
Effects on Grading, %
|
|
Attendance
|
1
|
10
|
|
Midterm
|
|
|
|
Quiz
|
|
|
|
Homework
|
6
|
30
|
|
Term Paper/Project
|
1
|
40
|
|
Laboratory Work
|
|
|
|
Practices
|
|
|
|
Tutorial
|
|
|
|
Seminar
|
|
|
|
Presentation
|
1
|
20
|
|
Field Study
|
|
|
|
Final Exam
|
|
|
|
TOTAL
|
|
100
|
|
Effects of Midterm on Grading, %
|
|
50
|
|
Effects of Final on Grading, %
|
|
50
|
|
TOTAL
|
|
100
|
|
ECTS/
WORKLOAD TABLE
|
Activities
|
Count
|
Hours
|
Total
Workload
|
|
Lecture
|
13
|
2
|
26
|
|
Midterm
|
|
|
|
|
Quiz
|
|
|
|
|
Homework
|
6
|
4
|
24
|
|
Term Paper/Project
|
1
|
45
|
45
|
|
Laboratory Work
|
|
|
26
|
|
Practices
|
|
|
|
|
Tutorial
|
|
|
|
|
Seminar
|
|
|
|
|
Presentation
|
1
|
1
|
1
|
|
Field Study
|
|
|
|
|
Final Exam
|
1
|
3
|
3
|
|
Individual Study for Mid term Exam (Preperation for lecture+exam)
|
|
|
|
|
Individual Study for Final Exam
|
|
|
|
|
Total Workload
|
|
|
125
|
|
Total Workload/25
|
|
|
150/25
|
|
Course ECTS Credits
|
|
|
5
|
Weekly Course Plan: The weekly course plan may vary according to the course speed. The related chapter of the book (_ch) is shown in parentheses:
|
Week
|
Topics
|
Course Outcomes
|
|
1
|
Introduction of the Course and Meeting
|
|
|
2
|
Basic Conceptual Features and Historical Development
|
I
|
|
3
|
Conventional Data Mining and Data Warehouse
|
I,II,III
|
|
4
|
Data Components in Big Data
|
I,II,III,IV
|
|
5
|
Big Data Application Examples
|
I,II,III,IV
|
|
6
|
Big Data Technologies Overview
|
I,II,III,IV
|
|
7
|
Architecture of Big Data Technologies
|
I,II,III,IV
|
|
8
|
Python Coding Practice in the Scope of Big Data Management
|
I,II,III,IV
|
|
9
|
Case Study I
|
I,II,III,IV
|
|
10
|
Project
|
I,II,III,IV
|
|
11
|
Big Data Analytics I
|
I,II,III,IV
|
|
12
|
Big Data Analytics II
|
I,II,III,IV
|
|
13
|
Case Study II
|
I,II,III,IV
|
|
14
|
Review and Discussion of Learned
|
I,II,III,IV
|
Relationship between the Course and the MANAGEMENT INFORMATION SYSTEMS Curriculum
|
|
Program Outcomes
|
Level of Contribution
|
|
1
|
2
|
3
|
|
a
|
To use concepts and theories related to different basic functions of business, to analyze and solve related process problems.
|
X
|
|
|
|
b
|
As managers of the business, making decisions using appropriate analytical and quantitative techniques.
|
X
|
|
|
|
c
|
Having research skills on how to obtain the necessary resources to evaluate and solve business problems.
|
X
|
|
|
|
d
|
When adapting information technology applications, be aware of relevant environmental, social and ethical rules
|
|
|
X
|
|
e
|
Using a foreign language and communicating verbally and in writing with colleagues from all over the world to follow new developments in business, management and information.
|
|
|
X
|
|
f
|
To demonstrate teamwork and leadership skills required in business environment and project management.
|
|
|
X
|
|
g
|
For information technology applications - for interdisciplinary work that can combine social and technical areas - to produce and analyze strategies that will improve operational efficiency, improve creativity and innovation.
|
|
|
X
|
|
h
|
Identify software, hardware, infrastructure, database and communication requirements according to business requirements, design the necessary components, make the selection, manage the system.
|
|
X
|
|
|
i
|
To create a project plan for an information system project, to analyze and document the necessary needs, to dominate the systematic database analysis, design and implementation stages, to give technical and managerial contributions, to take responsibility and to manage effectively.
|
|
|
X
|
|
j
|
To know programming and database logic and to use a modern programming language.
|
|
|
X
|
|
k
|
To have mastery of administrative / functional applications of enterprise information systems. To have knowledge about types of enterprise software, software selection and purchase decision, to plan and manage software development processes.
|
|
|
X
|
1: Small, 2: Partial, 3: Full
Programme Outcomes & Course Outcomes Connectivity Matrix
(Relationship between the Course and the MANAGEMENT INFORMATION SYSTEMS Curriculum)
|
|
|
I
|
II
|
III
|
IV
|
|
a
|
To use concepts and theories related to different basic functions of business, to analyze and solve related process problems.
|
1
|
1
|
2
|
2
|
|
b
|
As managers of the business, making decisions using appropriate analytical and quantitative techniques.
|
1
|
2
|
2
|
2
|
|
c
|
Having research skills on how to obtain the necessary resources to evaluate and solve business problems.
|
1
|
1
|
1
|
1
|
|
d
|
When adapting information technology applications, be aware of relevant environmental, social and ethical rules
|
3
|
1
|
2
|
1
|
|
e
|
Using a foreign language and communicating verbally and in writing with colleagues from all over the world to follow new developments in business, management and information.
|
2
|
2
|
2
|
2
|
|
f
|
To demonstrate teamwork and leadership skills required in business environment and project management.
|
1
|
1
|
2
|
2
|
|
g
|
For information technology applications - for interdisciplinary work that can combine social and technical areas - to produce and analyze strategies that will improve operational efficiency, improve creativity and innovation.
|
3
|
2
|
3
|
3
|
|
h
|
Identify software, hardware, infrastructure, database and communication requirements according to business requirements, design the necessary components, make the selection, manage the system.
|
3
|
3
|
3
|
3
|
|
i
|
To create a project plan for an information system project, to analyze and document the necessary needs, to dominate the systematic database analysis, design and implementation stages, to give technical and managerial contributions, to take responsibility and to manage effectively.
|
3
|
3
|
3
|
3
|
|
j
|
To know programming and database logic and to use a modern programming language.
|
1
|
1
|
2
|
2
|
|
k
|
To have mastery of administrative / functional applications of enterprise information systems. To have knowledge about types of enterprise software, software selection and purchase decision, to plan and manage software development processes.
|
2
|
2
|
2
|
3
|
|
Prepared by
ASSIST. PROF. MASOUD SHAHMANZARI
|
Date
05.10.2020
|
Signature
|