IIBA IIBA Certifications CBDA Questions & Answers

• Question 61:

  An analyst is interested in providing a visual diagram to compare and contrast the characteristics of four different solution options. Each option should be represented by their cost, value, and risk level. What type of chart would accomplish this task?

  A. Bubble

  B. Waterfall

  C. Pie

  D. Bullet

  Correct Answer: A

  A bubble chart is a type of chart that displays three dimensions of data: the x-axis, the y-axis, and the size of the bubble. A bubble chart can be used to compare and contrast the characteristics of different solution options by plotting their cost, value, and risk level on the three axes. For example, a solution option with a high cost, high value, and low risk would be represented by a large bubble on the upper left corner of the chart, while a solution option with a low cost, low value, and high risk would be represented by a small bubble on the lower right corner of the chart. A bubble chart can help the analyst and the stakeholders to visualize the trade-offs and benefits of each solution option and to select the most optimal one based on the business objectives and constraints.

• Question 62:

  The data analysis completed by the analytics team points to three potential options that could be recommended by the team each of which will help their organization meet their desired goal. Given that there is no significant difference in the results that each option would provide, the team will reach a final recommendation by determining value to be delivered to specific parts of the organization and:

  A. Within the functional unit with the most staff

  B. By which manager wants the change the most

  C. Assessing the impact of change for each one

  D. By optaining a decision by senior management

  Correct Answer: C

  According to the IIBA's Guide to Business Data Analytics, one of the steps in the data analysis process is to use the results to influence business decision making. This involves evaluating the feasibility, viability, and desirability of the potential options or solutions that are derived from the data analysis, and recommending the best option or solution that aligns with the business goals and objectives1. To evaluate the feasibility, viability, and desirability of the options or solutions, the data analysis team should consider the value to be delivered to specific parts of the organization and the impact of change for each one. The value to be delivered refers to the benefits, outcomes, or improvements that the option or solution will provide to the stakeholders, customers, or processes of the organization. The impact of change refers to the costs, risks, or challenges that the option or solution will entail for the implementation, adoption, or maintenance of the organization. By assessing the value and the impact of each option or solution, the data analysis team can compare and contrast the trade-offs, pros and cons, and strengths and weaknesses of each option or solution, and select the one that maximizes the value and minimizes the impact for the organization2.

  The other options are not correct criteria for reaching a final recommendation. The functional unit with the most staff, the manager who wants the change the most, and the senior management are not relevant factors for evaluating the options or solutions, as they do not reflect the value or the impact of the options or solutions. The functional unit with the most staff may not be the most affected or the most important part of the organization for the data analysis project. The manager who wants the change the most may not have the authority, influence, or expertise to make the best decision for the organization. The senior management may not be the only or the final decision makers for the data analysis project, as they may delegate, consult, or collaborate with other stakeholders or experts.

• Question 63:

  A data dictionary is being developed for a dataset describing a company's customer base. Within the data dictionary, which of the following represents a composite data element?

  A. Street address

  B. First name

  C. Total sale

  D. Birthdate

  Correct Answer: A

  A composite data element is a data element that is made up of smaller units called sub-elements, which are separated by a sub-element separator character, such as a colon (:). For example, ITEMNO is a composite data element that consists of three sub-elements: part number, aisle number, and bin number. A street address is also a composite data element that can consist of sub-elements such as street number, street name, city, state, and zip code. First name, total sale, and birthdate are simple data elements that do not have sub-elements.

• Question 64:

  A consumer product company has recently seen decline in sales in their athletic wear over the last 3 quarters. Along with a customer satisfaction survey on their athletic wear products, a study on the competitive market has been initiated. The analyst working has created a dashboard, integrating the results from the market study with customer feedback. On reviewing with the analytics manager, the feedback received was that the visuals were powerful, but the dashboard lacked narrative.What does the manager mean by this?

  A. Commentary around why each visual was selected to depict the data will provide context

  B. More commentary needs to be added to add value to the audience

  C. Adding a story example will augment the experience for the audience

  D. Insights need to be supported by context and comments to engage the audience

  Correct Answer: D

  According to the Guide to Business Data Analytics, a narrative is a way of communicating the results of data analysis in a clear, concise, and compelling manner. A narrative should include the following elements: the purpose of the analysis, the main findings and insights, the implications and recommendations, and the evidence and reasoning. A narrative should also use appropriate language, tone, and style for the intended audience and medium. A narrative can enhance the impact and value of the data analysis by providing context, explanation, and interpretation of the data, as well as by highlighting the key messages and actions. A dashboard that lacks narrative may not be able to convey the full meaning and significance of the data, and may not be able to engage the audience or influence their decision-making.

• Question 65:

  The results for a certification exam were revealed in percentage and percentile. How would you infer the results for an attendee at: 75%, 90th percentile?

  A. While the attendee's exam score was 90/100. the attendee did better than 75% of the attendees

  B. While the attendee's exam score was 90/100. the attendee did better than 25% of the attendees

  C. While the attendee's exam score was 75/100. the attendee did better than 10% of the attendees

  D. While the attendee's exam score was 75/100. the attendee did better than 90% of the attendees

  Correct Answer: D

  A percentage is a way of expressing a number as a fraction of 100, while a percentile is a way of expressing a number as a rank or position in a distribution of values. A percentage tells us how much of something there is, while a percentile

  tells us how well something performed compared to others. To infer the results for an attendee at 75%, 90th percentile, we need to understand what these two numbers mean.

  75% means that the attendee scored 75 out of 100 possible points on the exam. This is the absolute score of the attendee, which does not depend on how others performed.

  90th percentile means that the attendee scored higher than 90% of all the attendees who took the exam. This is the relative score of the attendee, which depends on how others performed. For example, if there were 1000 attendees, the 90th

  percentile would mean that the attendee scored higher than 900 attendees, and lower than 100 attendees.

  Therefore, the correct inference is that while the attendee's exam score was 75/100, the attendee did better than 90% of the attendees. This means that the attendee's score was above average, and that the exam was relatively difficult or had

  a low pass rate. References:

  Difference Between Percentage and Percentile | Major DifferencesBYJU'S, BYJU'S, accessed on January 20, 2024.

  Difference Between Percentage and Percentile (with Examples and Comparison Chart)Key Differences, Key Differences, accessed on January 20, 2024.

  Certification in Business Data Analytics (IIBA瓹BDA), IIBA, accessed on January 20, 2024.

• Question 66:

  A pharmaceutical company is conducting research to determine whether a new medicine in development is more successful in reducing the pain associated with rheumatoid arthritis then their current drug in the market. A group of volunteers are selected for the research. One set of participants is provided the existing drug while a second set of participants is given the new drug.Which technique is being applied?

  A. Observational design

  B. Block design

  C. A/B testing

  D. Natural experiment

  Correct Answer: C

  A/B testing, also known as randomized controlled trial or split testing, is a technique that compares the outcomes of two or more groups that are randomly assigned to different treatments or interventions. The purpose of A/B testing is to measure the causal effect of the treatments on the outcomes of interest, such as pain reduction in this case. A/B testing can help determine whether the new medicine is more effective than the existing drug by comparing the average pain scores of the two groups of participants after the treatment.

• Question 67:

  Analytics is being used to estimate the number of machine breakdowns a company will experience next year. The business analyst provides an optimistic estimate of 10 breakdowns, a pessimistic estimate of 100 breakdowns, and a most likely value of 50 breakdowns.What type of estimation is being used?

  A. Parametric Estimation

  B. PERT

  C. Top-down

  D. Delphi

  Correct Answer: B

  According to the Guide to Business Data Analytics, PERT (Program Evaluation and Review Technique) is a type of estimation that uses three values: optimistic, pessimistic, and most likely. The PERT estimate is calculated as the weighted average of these three values, with more weight given to the most likely value. PERT can be used to estimate the duration, cost, or other variables of a project or activity, taking into account the uncertainty and variability of the data. PERT can help provide a realistic and reliable estimate based on the available information.

• Question 68:

  A large bank has recently revamped their website, adding additional features such as financial investment opportunities, spending activity, and supporting reports. Which question will add value when evaluating how the website is being used?

  A. What is the customer satisfaction rating across the branches?

  B. What are the top keywords used in searches made within the website?

  C. What is the customer retention rate since the website launch?

  D. How many articles were published since the website launch?

  Correct Answer: C

  Customer retention rate is a measure of how many customers continue to use a product or service over a given period of time. It is an important indicator of customer loyalty, satisfaction, and value. Customer retention rate can help the bank evaluate how the website is being used by comparing the number of customers who visited the website before and after the launch of the new features. A high customer retention rate would suggest that the new features are attractive, useful, and engaging for the customers, while a low customer retention rate would indicate that the new features are not meeting the customers' needs or expectations. Customer retention rate can also help the bank identify the segments of customers who are more or less likely to use the website, and tailor their marketing and communication strategies accordingly.

• Question 69:

  Interested in ensuring that analytics continues to contribute value to the overall organization, the lead analyst suggests developing a long term plan to define how the enterprise will identify, store, manage, share, and use its data long-term.The analyst is proposing the development of a:

  A. Data roadmap

  B. Business strategy

  C. Data strategy

  D. Data management plan

  Correct Answer: C

  A data strategy is a long-term plan that defines how the enterprise will identify, store, manage, share, and use its data to achieve its business goals and objectives1. A data strategy aligns the data vision, mission, principles, and policies with the business strategy, and guides the data governance, data quality, data architecture, data security, data integration, data analytics, and data culture of the organization2. A data strategy helps the organization to leverage its data as a strategic asset, to create value, to improve performance, and to gain competitive advantage3.

  A data roadmap is a document that outlines the specific actions, milestones, deliverables, and timelines for implementing the data strategy. A data roadmap is a tactical tool that helps the organization to prioritize, coordinate, and communicate its data initiatives, and to track its progress and outcomes. A data roadmap is not a long-term plan, but a dynamic and flexible plan that can be updated and revised as the data strategy evolves.

  A business strategy is a high-level plan that defines how the enterprise will achieve its vision, mission, and goals in a competitive market. A business strategy sets the direction, scope, and value proposition of the organization, and guides its decisions on resource allocation, product development, customer segmentation, pricing, marketing, and differentiation. A business strategy is not a plan that defines how the enterprise will identify, store, manage, share, and use its data, but a plan that defines how the enterprise will create and sustain value for its stakeholders.

  A data management plan is a document that describes the data that will be collected, generated, or used in a specific project, and how the data will be handled, stored, preserved, shared, and reused during and after the project. A data management plan is a operational tool that helps the project team to comply with the data policies, standards, and best practices of the organization, and to ensure the quality, integrity, security, and accessibility of the data. A data management plan is not a long-term plan, but a project-specific plan that can be modified and updated as the project progresses.

• Question 70:

  An organization has a customer database of 3000 customers and has accumulated 5 years of sales data. They want to make decisions about which products to retire and which to continue to offer. Management has turned to the analytics team to analyze the data and provide recommendations. The analytics team develops a survey to send to randomly selected customers.This is an example of:

  A. Data Wrangling

  B. Data Manipulation

  C. Data Grouping

  D. Data Sampling

  Correct Answer: D

  Data sampling is the process of selecting a subset of data from a larger population to represent the characteristics of the whole population. Data sampling is often used when the population is too large or costly to collect data from every individual. Data sampling can help reduce the time, cost, and complexity of data analysis, while maintaining the validity and reliability of the results. Data sampling can also help avoid biases and errors that may arise from collecting data from the entire population. Data sampling can be done using various methods, such as random sampling, stratified sampling,cluster sampling, or convenience sampling, depending on the research objectives and the availability of data. In this example, the analytics team develops a survey to send to randomly selected customers, which is a form of data sampling. The survey aims to collect data from a representative sample of customers that can reflect the preferences and opinions of the entire customer population. The survey data can then be used to analyze the performance and demand of different products, and provide recommendations to management.