AIN3701 – Automation and Data Analysis | January/February
2026 Supplementary Exam Memo (UNISA South Africa)
,1. What is the primary function of automation in data analysis?
• A) To eliminate the need for data
• B) To enhance the speed and accuracy of analysis
• C) To replace human analysts completely
• D) To limit the types of data that can be analyzed
Correct Option: B
Rationale: Automation in data analysis refers to the use of technology to improve the
speed and accuracy of processing and analyzing data. It allows for the rapid execution
of repetitive tasks and reduces human error, enabling more efficient data-driven
decision-making.
2. Which of the following tools is commonly used for data automation?
• A) Microsoft Excel
• B) Python scripting
• C) Google Docs
• D) PowerPoint
Correct Option: B
Rationale: Python scripting is widely recognized for its capabilities in data automation,
including data extraction, transformation, and loading (ETL processes). It offers libraries
such as Pandas and NumPy that facilitate efficient data manipulation and analysis.
3. In data analysis, what does the term "ETL" stand for?
• A) Extract, Transform, Load
• B) Evaluate, Test, Learn
• C) Enhance, Track, Log
• D) Extract, Transfer, Load
Correct Option: A
Rationale: ETL stands for Extract, Transform, Load. It is a process used in data
warehousing and analytics to collect data from various sources, transform it into a
suitable format, and load it into a destination system, ensuring that data is clean and
accessible for analysis.
, 4. Which of the following methods is most effective for cleaning data before
analysis?
• A) Data sampling
• B) Data validation techniques
• C) Data visualization
• D) Data encryption
Correct Option: B
Rationale: Data validation techniques are crucial for cleaning data as they help identify
and rectify errors or inconsistencies in the dataset before analysis. This step ensures
the integrity of data, leading to more accurate insights and decisions.
5. What role does a data pipeline play in automation and data analysis?
• A) It stores data securely.
• B) It visualizes data for end-users.
• C) It automates the flow of data from source to analysis.
• D) It manually processes data entries.
Correct Option: C
Rationale: A data pipeline automates the process of moving data from one system to
another—typically from data sources to analytical tools. It streamlines workflows,
reduces latency, and ensures that data is continuously updated and ready for analysis.
6. What type of analysis involves predicting future values based on historical data?
• A) Descriptive Analysis
• B) Predictive Analysis
• C) Prescriptive Analysis
• D) Diagnostic Analysis
Correct Option: B
Rationale: Predictive analysis uses statistical algorithms and machine learning
techniques to identify the likelihood of future outcomes based on historical data. This
analysis is crucial in forecasting trends and making proactive decisions.
7. In the context of data analysis, what does "big data" refer to?
• A) Data that is difficult to process using traditional methods
• B) Data that is always structured
2026 Supplementary Exam Memo (UNISA South Africa)
,1. What is the primary function of automation in data analysis?
• A) To eliminate the need for data
• B) To enhance the speed and accuracy of analysis
• C) To replace human analysts completely
• D) To limit the types of data that can be analyzed
Correct Option: B
Rationale: Automation in data analysis refers to the use of technology to improve the
speed and accuracy of processing and analyzing data. It allows for the rapid execution
of repetitive tasks and reduces human error, enabling more efficient data-driven
decision-making.
2. Which of the following tools is commonly used for data automation?
• A) Microsoft Excel
• B) Python scripting
• C) Google Docs
• D) PowerPoint
Correct Option: B
Rationale: Python scripting is widely recognized for its capabilities in data automation,
including data extraction, transformation, and loading (ETL processes). It offers libraries
such as Pandas and NumPy that facilitate efficient data manipulation and analysis.
3. In data analysis, what does the term "ETL" stand for?
• A) Extract, Transform, Load
• B) Evaluate, Test, Learn
• C) Enhance, Track, Log
• D) Extract, Transfer, Load
Correct Option: A
Rationale: ETL stands for Extract, Transform, Load. It is a process used in data
warehousing and analytics to collect data from various sources, transform it into a
suitable format, and load it into a destination system, ensuring that data is clean and
accessible for analysis.
, 4. Which of the following methods is most effective for cleaning data before
analysis?
• A) Data sampling
• B) Data validation techniques
• C) Data visualization
• D) Data encryption
Correct Option: B
Rationale: Data validation techniques are crucial for cleaning data as they help identify
and rectify errors or inconsistencies in the dataset before analysis. This step ensures
the integrity of data, leading to more accurate insights and decisions.
5. What role does a data pipeline play in automation and data analysis?
• A) It stores data securely.
• B) It visualizes data for end-users.
• C) It automates the flow of data from source to analysis.
• D) It manually processes data entries.
Correct Option: C
Rationale: A data pipeline automates the process of moving data from one system to
another—typically from data sources to analytical tools. It streamlines workflows,
reduces latency, and ensures that data is continuously updated and ready for analysis.
6. What type of analysis involves predicting future values based on historical data?
• A) Descriptive Analysis
• B) Predictive Analysis
• C) Prescriptive Analysis
• D) Diagnostic Analysis
Correct Option: B
Rationale: Predictive analysis uses statistical algorithms and machine learning
techniques to identify the likelihood of future outcomes based on historical data. This
analysis is crucial in forecasting trends and making proactive decisions.
7. In the context of data analysis, what does "big data" refer to?
• A) Data that is difficult to process using traditional methods
• B) Data that is always structured
