Chapter 7 Information requirement analysis.pptx

System analysis and design

1. Course: CSC1108 - System Analysis & Design Semester: January 2024 Lecturer: Ms Jayashiry Morgan

2. Recap: Activity Planning Control Two tools for Project Planning and Control: Gantt Chart PERT diagram Tasks involved in the project: Task Identification Task Sequencing Estimation of Time and Resources Task Assignment Schedule Development Monitoring and Tracking Adjustments and Fine-tuning

3. Chapter 7: Information Requirements Analysis: Sampling And Investigating Data

4. Learning Outcome By end of this session, students should be able to explain: The importance of information requirements analysis in the system development life cycle, Various sampling techniques, Process of investigating data through interviews, questionnaires, and observation methods Descriptive statistics and inferential statistics.

5. Information Requirement Analysis is the process of determining the data and information needs of an organization or system to support its goals and objectives. This involves identifying and defining the type, format, and content of the data and information required, as well as the sources of this information. Purpose: to provide a comprehensive understanding of the information that is necessary to support the goals and objectives of a system, organization, or process to ensure that all necessary information is available, accurate, and accessible.

6. Process of Information Requirements Analysis Includes: Identifying stakeholders Defining the business requirements Determining the data sources Evaluating the existing data Defining data and information requirements Designing the information architecture Validation and verification

7. Information Requirement Analysis Sampling Investigating Data

8. Sampling Technique Random Sampling Stratified Sampling Cluster Sampling Convenience Sampling

9. Sampling Technique Random Sampling Stratified Sampling Cluster Sampling Convenience Sampling

10. #1 Random Sampling Involves selecting a sample from a population in such a way that each member of the population has an equal chance of being selected. This technique helps in avoiding biases and ensures that the sample is representative of the entire population. Example: Simple random sampling, systematic sampling, and stratified random sampling.

11. Sampling Technique Random Sampling Stratified Sampling Cluster Sampling Convenience Sampling

12. #2 Stratified Sampling In stratified sampling, the population is divided into subgroups or strata based on certain characteristics. Samples are then randomly selected from each stratum proportionate to its size in the population. This method ensures representation from all segments of the population, making it useful when there are significant variations within the population.

13. Sampling Technique Random Sampling Stratified Sampling Cluster Sampling Convenience Sampling

14. #3 Cluster Sampling Involves dividing the population into clusters or groups. A random sample of clusters is then selected, and data is collected from all elements within the chosen clusters. This technique is advantageous when it is difficult to obtain a complete list of the population but relatively easy to access clusters.

15. Sampling Technique Random Sampling Stratified Sampling Cluster Sampling Convenience Sampling

16. #4 Convenience Sampling Involves selecting subjects based on their easy availability and accessibility to the researcher. While this method is convenient, it may introduce bias into the sample, as it does not ensure representative selection from the population.

17. Types Of Sampling Techniques Watch this video: Click Here

18. Investigating Data Interview Questionnaires Observation

19. Investigating Data Interview Questionnaires Observation

20. #1 Interview Interviews are structured conversations conducted with stakeholders, users, and subject matter experts to gather information about their requirements and preferences. Open-ended questions allow for detailed responses , while closed-ended questions can be used for specific data gathering . Interview techniques such as structured interviews, semi-structured interviews, and unstructured interviews can be employed based on the information needed and the nature of the stakeholders.

21. Investigating Data Interview Questionnaires Observation

22. #2 Questionnaires Questionnaires are written instruments containing a series of questions designed to gather specific information from respondents. They can be administered in person, through mail, or electronically, depending on the target audience. Closed-ended questions provide quantifiable data , while open-ended questions allow for more detailed responses .

23. Investigating Data Interview Questionnaires Observation

24. #3 Observation Observation involves directly observing users or processes in their natural environment to understand their behaviors, interactions, and requirements . This method provides firsthand insights into how tasks are performed and can uncover implicit requirements that may not be articulated through interviews or questionnaires.

25. Data Analysis Techniques Descriptive Statistics Inferential Statistics

26. Data Analysis Techniques Descriptive Statistics Inferential Statistics

27. Descriptive Statistics Descriptive statistics, such as mean, median, mode, standard deviation, and variance, are used to summarize and describe the characteristics of a dataset. These statistics provide valuable insights into the central tendency, dispersion, and distribution of the data.

28. Data Analysis Techniques Descriptive Statistics Inferential Statistics

29. Inferential Statistics Inferential statistics involve making inferences or predictions about a population based on sample data. Techniques such as hypothesis testing, regression analysis, and analysis of variance (ANOVA) are used to draw conclusions and make generalizations about the population.

30. Conclusion Information requirements analysis through sampling and investigating data is essential for understanding the needs of stakeholders and defining the data requirements of a system accurately .

31. Watch Watch this video: Click Here

32. Class Activity 1: Discussion Divide into 2 groups. Each group will be given a scenario. Answer to the questions based on the scenario given to each group. You will discuss about your findings to the other group, and vice versa. Time given to prepare: 15 minutes Discussion time: 10 minutes

33. Scenario #1 You are a data analyst hired by a healthcare organization to improve patient care services through the implementation of a new electronic health record (EHR) system. Your task is to conduct information requirements analysis to understand the data needs of healthcare providers, administrative staff, and patients. Question : As the appointed data analyst for the healthcare organization, outline your plan for sampling and investigating data to gather crucial information for the development of the new electronic health record (EHR) system. Scenario #2 You are a consultant working with a retail chain to enhance their inventory management system. The company is experiencing issues with stockouts and overstocking, leading to revenue loss and inefficient operations. As part of your consulting project, you need to conduct information requirements analysis to understand the data needs for improving inventory management. Question : As the consultant tasked with improving the inventory management system for the retail chain, outline your plan for sampling and investigating data to gather essential information for system enhancement.