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.