ECM380 : Data Analysis1

Department

Department of E-commerce and data analysis

Academic Program

Bachelor in E-commerce and data analysis

Type

Compulsory

Credits

03

Prerequisite

ECM286

Overview

The Data Analysis 1 course identifies the general foundations of data analysis as an important part of improving the quality and effectiveness of performance. It also clarifies the concept of data analysis, its objectives, elements, functions, development, implementation, requirements, and its relationship to database management. It also describes how to analyze data, analyzes and interprets case studies, and how to benefit from them. It also uses technology and technology to create a network model for data analysis.

Intended learning outcomes

A. Knowledge and understanding:

  •  Knows data analysis, its method, how to deal with it, and its impact on achieving the goals of organizations.
  • Explains data analysis requirements
  • List the differences between data analysis processes
  • The student learns about the use of data analysis as an important part of improving the quality and effectiveness of performance
  •  the student determines what is required of the practical case analysis.
  B. Mental skills:
  •  Explain the relationship between data analysis requirements and the reasons for success and failure
  • To link the information aggregator and data analysis
  •  Analyze the elements of data analysis
  •  Apply the rules of the grid model to the data analysis process
  •  Analyze the practical reality of the study case.
  C- Scientific and professional skills:
  • Participate in the application of transformation mechanisms in dealing with how to analyze data in organizational processes
  •  Create solutions to problems facing the data analysis process.
  •  Creates a practical model for the data analysis management strategy.
  •  The data analysis model is applied in any organization
  •  Deals with technological means and information technology to build a network model for data analysis.
D- General Skills:
  • Participate in the application of the mechanisms of transition to data analysis practices in organizational processes
  • Create solutions to problems for data analysis.
  • Creates a practical model for the data analysis strategy
  • The data analysis model is applied in any organization
  • Deals with the technological means to build the network model for data analysis.

Teaching and learning methods

1. Study lectures.

2. Participation during the lecture.

3. Research papers.

4. Case study.

Methods of assessments

  1. midterm exam 20%
  2. oral exam 10%
  3. practical exam 10%
  4. final exam 60%

Computer Fundamentals (ECM181)
Electronic Commerce Fundamentals (ECM280)
Databases (ECM282)
systems analysis and design 1 (ECM286)
Data Analysis1 (ECM380)