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ASSESSMENT QUESTIONS

MULTIPLE CHOICE QUESTIONS (1 mark each)​

  1. Which of the following is NOT a type of data used by organizations? a) Structured data b) Unstructured data c) Certified data d) Semi-structured data

  2. Which of the following is human-generated data? a) Sensor readings b) System performance metrics c) Social media posts d) Log files

  3. Which of the following is machine-generated data? a) Email messages b) Social media posts c) Transaction data d) Website content created by users

  4. Which level of decision making involves day-to-day operational choices? a) Strategic b) Tactical c) Operational d) Analytical

  5. What is a common ethical issue related to data collection? a) System performance b) Data storage costs c) Use of cookies and transactional data d) Database management

  6. Which of the following is a core aim of data science? a) Increasing data volume b) Extracting actionable intelligence to improve business performance c) Creating more complex databases d) Eliminating the need for human analysis

  7. What is NOT typically a skill required for data science? a) Mathematics and statistics b) Programming and scripting skills c) Hardware engineering d) Business knowledge

  8. Which data format is commonly used for structured data exchange between systems? a) PDF b) JSON c) MP3 d) GIF

  9. Which of the following is a sub-discipline in the data science field? a) Virtual reality b) Machine learning c) Project management d) Print media

  10. What is predictive modeling used for in data science? a) Analyzing past events only b) Forecasting and identifying trends c) Creating visual reports d) Organizing databases

  11. What is a potential organizational implication of failing to adequately protect data? a) Increased market share b) Legal actions and financial impact c) Better customer relationships d) Improved staff morale

  12. What is the concept of 'secure by design' related to? a) Physical office security b) Developing systems that inherently protect data c) Marketing strategy d) Website aesthetics

  13. What is the primary purpose of data mining? a) Extracting raw materials b) Finding anomalies, patterns and relationships between data sets c) Creating new data d) Permanently deleting old data

  14. Which of the following is used to automate data science processes? a) Microsoft Word b) Adobe Photoshop c) Python programming language d) Email clients

  15. What does the process of turning data into visual information help with? a) Reducing data storage needs b) Eliminating the need for analysis c) Communicating information effectively to stakeholders d) Encrypting sensitive information

  16. When analyzing business processes, what is an important consideration for user interface design? a) Using the most expensive software b) Creating user-friendly and functional interfaces c) Using only text-based interactions d) Limiting user customization options

  17. What is a key challenge when working with unstructured data? a) It's too organized b) It's more difficult to analyze than structured data c) It's always smaller in volume d) It's always more secure

SHORT ANSWER QUESTIONS (5 marks each)​

  1. Explain the value of data and information for strategic, tactical, and operational decision making in organizations. (5 marks)

  2. Describe three ways in which data and information can be used to support business processes, with examples. (5 marks)

  3. Discuss the social and ethical implications of collecting and using customer data for business processes. (5 marks)

  4. Explain the concept of cybersecurity management and three common threats to data and information. (5 marks)

  5. Describe the core aims of data science and how it helps to improve business performance. (5 marks)

  6. Explain the difference between structured and unstructured data, providing examples of each and their implications for business analysis. (5 marks)

  7. Describe how predictive modeling can be used to support business processes, with examples. (5 marks)

  8. Explain the importance of data visualization in communicating information to stakeholders. (5 marks)

LONG ANSWER QUESTIONS (10 marks each)​

  1. Analyze how the exponential growth in the amount of data generated has impacted businesses, and discuss the challenges and opportunities this presents for organizations. Include references to relevant data handling techniques and technologies. (10 marks)

  2. Compare and contrast the roles of data engineers, data scientists, and business analysts in supporting an organization's data strategy. Explain how these roles collaborate to turn data into valuable business insights. (10 marks)

  3. Design a data science solution to address a specific business problem of your choice. Your answer should include:

    • A clear description of the business problem
    • The data sources and types required
    • The data science techniques you would apply
    • How the solution would support decision making
    • Potential challenges and considerations (10 marks)

  4. Critically analyze the importance of addressing user and system requirements when designing data science solutions. Your answer should consider user engagement, data quality risks, meaningful data output, and testing phases, with specific examples. (10 marks)