IIBA CBDA Exam Actual Questions

Name: Certification in Business Data Analytics
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SKU: CBDA
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The questions for CBDA were last updated on Oct 3, 2024.

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Question No. 1

A large retail chain has asked their analytics team to complete a study on their customers' purchasing patterns. The analyst assigned to the study has decided to draw further insight by grouping customers based on their purchasing habits. This clustering approach is an example of:

AUntrained learning

BTrained learning

CUnsupervised learning

DSupervised learning
Explanation:
Unsupervised learning is a category of data analysis techniques that does not require labeled data or predefined outcomes. Unsupervised learning aims to discover patterns, structures, or relationships in the data without any guidance or supervision. Clustering is a common example of unsupervised learning, where the data is grouped into clusters based on some similarity or distance measure. Clustering can help reveal customer segments, market trends, or product preferences, among other insights.

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Correct Answer: C

Question No. 2

A clinical research organization is using predictive analytics to improve patient safety and decrease costs on its clinical trials. To ensure that a standard set of tools/techniques is identified and best practices adhered to, teams are required to create scenarios to generate appropriate data for initial analysis. This practice is required because it is almost certain that data will be difficult to come by for most research. Which concern would lead the team to establish scenario development as a required technique?

AData validity

BData privacy

CData reliability

DData reproducibility
Explanation:
Data validity refers to the extent to which data accurately represents the phenomenon or concept that it is intended to measure1. Data validity is essential for predictive analytics, as it affects the quality and credibility of the analysis results and the subsequent decisions or actions based on them. If data is invalid, the predictions may be inaccurate, misleading, or irrelevant.However, data validity may be challenging to ensure in clinical research, as data may be scarce, incomplete, inconsistent, or subject to errors or biases2. Therefore, the team may establish scenario development as a required technique to address this concern.Scenario development is a form of document analysis that involves creating hypothetical situations or stories based on assumptions, evidence, and logic to explore the possible outcomes or implications of a problem or opportunity3.Scenario development can help the team generate appropriate data for initial analysis by simulating different conditions, variables, or events that may affect the clinical trials, and by testing the validity of the data against the scenarios4.

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Correct Answer: A

Question No. 3

A consumer products company is interested in finding ways to innovate utilizing business analytics. The team is reviewing a database of customer complaints. Interested in knowing how the organization currently interacts with its customers, the analyst proposes the use of which technique?

ADocument analysis

BJourney map

CCurrent state assessment

DInterface analysis

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Correct Answer: B

A journey map is a visual representation of the interactions and experiences of a customer or stakeholder with an organization, product, or service over time. A journey map can help identify pain points, gaps, opportunities, and emotions along the customer journey. A journey map can also help understand the current state of the customer experience and how it can be improved or innovated using business analytics.

Question No. 4

While formulating the results from completed analysis, the analytics team is applying different techniques to determine an optimal solution to the specified business problem. Which of the following runs the risk of introducing bias in their decision making process?

AEvidenced-based decision making

BExpert judgement and experience

CCorrelations identified through artificial intelligence

DLetting the data tell the story

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Correct Answer: B

Expert judgement and experience are valuable sources of knowledge and insight for business data analytics, but they can also introduce bias in the decision making process. Bias is a tendency to favor or reject a certain perspective, outcome, or solution based on personal or subjective preferences, beliefs, or expectations. Bias can affect the quality, validity, and reliability of the data analysis and the resulting decisions. Some examples of bias that can affect expert judgement and experience are confirmation bias, availability bias, anchoring bias, and overconfidence bias. To avoid or minimize bias, business data analysts should apply critical thinking, data literacy, and ethical principles throughout the data analysis process. They should also seek diverse perspectives, challenge assumptions, validate findings, and communicate uncertainties and limitations.

Question No. 5

A company wants to run a monthly promotion on batteries that cost 15 cents each and sells for 50 cents. At this price, they typically sell 1000 batteries and generate a profit of 35 cents per battery for a total profit of $350. The analytics team was asked to test two price points - 20% off (i.e. a sale price of 40 cents) and 40% off (i.e., a sale price of 30 cents). The survey data completed by 10000 participants was analyzed and showed that a 20% savings would result in sales of 1200 batteries and the 40% savings would result in 1800 batteries being sold. The team's initial recommendation was to recommend the 40% discount. Now that they are validating their recommendations, they decide to:

AQuestion why management would only want them to test two price points

BChange their recommendation realizing they have been victims of linear bias

CRedo the survey looking for a larger sample size

DUse their original recommendation given that the volume of sales is much higher
Explanation:
Linear bias is a type of cognitive bias that assumes a linear relationship between two variables, when in fact the relationship may be more complex or nonlinear. In this case, the analytics team assumed that the higher the discount, the higher the sales and profit, without considering other factors that may affect customer behavior, such as price elasticity, perceived quality, or competition. By changing their recommendation, the team can avoid making a suboptimal decision that may result in lower profit or customer satisfaction.

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Correct Answer: B

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