Vendor: IIBA
Certifications: IIBA Certifications
Exam Code: CBDA
Exam Name: Certification in Business Data Analytics (CBDA)
Updated: May 24, 2026
Q&As: 150 ( View Details)
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VCE
The analytics team discovers there is an abundance of data available to them from various sources. They are excited about the potential of turning this data into usable information for their organization.They decide to focus the analytics work on:
A. Using the data that is easiest to collect in order to turn out reports quickly
B. Harnessing all the data and presenting various results to senior management
C. Harnessing all the data as long as the analysis meets key cost criteria
D. Using the data to answer a limited number of key questions
Correct Answer: D
According to the IIBA?Guide to Business Data Analytics, analytics work should be driven by well-defined business problems or opportunities that are aligned with the organization's strategic objectives1. Having an abundance of data does not necessarily mean that all of it is relevant, reliable, or useful for the analytics purpose. Therefore, the analytics team should focus on using the data to answer a limited number of key questions that are derived from the business context and that can generate actionable insights and outcomes. This approach can help the analytics team prioritize the most important data sources, methods, and tools, as well as avoid wasting time and resources on analysis that is not impactful or meaningful for the organization.
When reviewing the results of their analysis, the team is determining if the data supports their hypothesis and can be presented to decision makers. They are reviewing measures of variation, sample size and statistical significance. They realize that the p-value of 0.02 is lower than the initial target.This clearly indicates the team can:
A. Accept the null hypothesis and accept the alternative
B. Accept the null hypothesis and reject the alternative
C. Reject the null hypothesis in favor of the alternative
D. Reject the null hypothesis and reject the alternative
Correct Answer: C
According to the Guide to Business Data Analytics, a p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true. A p-value is used to make conclusions in hypothesis testing by comparing it to a significance level, which is the maximum probability of making a type I error (rejecting the null hypothesis when it is true). If the p-value is less than or equal to the significance level, then there is strong evidence against the null hypothesis and it is rejected in favor of the alternative hypothesis. If the p-value is greater than the significance level, then there is weak evidence against the null hypothesis and it is not rejected. In this situation, the team realizes that the p-value of 0.02 is lower than the initial target, which means that the probability of observing such a result under the null hypothesis is very low. This clearly indicates that the team can reject the null hypothesis in favor of the alternative hypothesis, as there is sufficient evidence to support their hypothesis.
An insurance company would like to develop a range of insurance products for different types of customers. The analytics team is asked to conduct some research and share their insights with senior management. Which technique would be useful to divide the customer base into groups?
A. Linear regression
B. Survey sampling
C. Factor analysis
D. K-means clustering
Correct Answer: D
K-means clustering is a technique that partitions a set of data points into a predefined number of clusters, based on their similarity or distance. This technique can be useful to divide the customer base into groups that have similar characteristics, preferences, or behaviors, and then design insurance products that cater to each group's needs and expectations. K-means clustering can also help identify outliers or anomalies in the customer data that may require further investigation or attention.
References: Guide to Business Data Analytics, page 58-59; CBDA lueprint, page 7; [Introduction to Business Data Analytics: A Practitioner View], page 17.
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