All About High Quality CBDA Vce

NEW QUESTION 1

An analytics team has completed some initial data analysis but is considering revising their research question based on their analysis findings. The team was concerned the original question was too broad. What outcome would lead the team to have this concern?

• A. Data once analyzed had significant data quality issues
• B. Data the team had planned to use was not available
• C. Difficult to identify the KPIs to measure
• D. The source data sets could not be merged

Answer: C

Explanation:
A research question is a clear and focused question that guides the data analytics process and defines the expected outcome or value of the analysis1. A research question that is too broad may lead to the concern of being difficult to identify the key performance indicators (KPIs) to measure, as KPIs are specific, quantifiable, and relevant metrics that indicate the progress and success of the analysis in relation to the research question23. A broad research question may also result in too much or too little data, unclear or conflicting objectives, or irrelevant or ambiguous results4. References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 202: Guide to Business Data Analytics, IIBA, 2020, p. 233: Key Performance Indicators: Developing, Implementing, and Using Winning KPIs, David Parmenter, 2015, p. 34: How to Write a Good Research Question, ThoughtCo, 2021, 1.

NEW QUESTION 2

A large car manufacturer is interested in comparing the number of sales for a specific model of electric car across all 50 US states.
The data analytics team sourced and acquired the data, and the business analyst created the model to compare sales across states.
In a meeting to review the results, the feedback received included several complaints concerning an inability to distinguish the number of sales per state. What model would result in such confusion?

• A. Bullet chart
• B. Dual axis chart
• C. Bar chart
• D. Pie chart

Answer: D

Explanation:
A pie chart is a circular chart that shows the proportion of each category in a whole by dividing the circle into slices. A pie chart would result in confusion when comparing the number of sales for a specific model of electric car across all 50 US states, because it is difficult to compare the angles and areas of the slices, especially when there are many categories with similar values. A pie chart also does not show the absolute values of each category, unless they are labeled or annotated12. A better alternative would be a bar chart, which can show the number of sales for each state along a common axis, making it easier to compare and rank the values3. References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 652: Storytelling with Data, Cole Nussbaumer Knaflic, 2015, p. 673: The Visual Display of Quantitative Information, Edward R. Tufte, 2001, p. 178.

NEW QUESTION 3

There were 7 students enrolled in the Introduction to Artificial Intelligence course. These were the student's scores from the final exam: 64, 70, 80, 80, 90, 98, 100
What is the mean and mode for the outlined scores?

• A. 83.14, 80
• B. 79.84, 81.40
• C. 80,80
• D. 80, 83.14

Answer: A

Explanation:
The mean is the average of all the scores, which is found by adding them up and dividing by the number of scores. The mode is the most frequent score, which is the one that occurs the most times. To find the mean and mode for the outlined scores, we can use the following steps:
•Arrange the scores in ascending order: 64, 70, 80, 80, 90, 98, 100
•Add up the scores: 64 + 70 + 80 + 80 + 90 + 98 + 100 = 582
•Divide the sum by the number of scores: 582 / 7 = 83.14
•The mean is 83.14
•Count how many times each score occurs: 64 occurs once, 70 occurs once, 80 occurs twice, 90 occurs once, 98 occurs once, 100 occurs once
•The score that occurs the most times is 80
•The mode is 80
Therefore, the mean and mode for the outlined scores are 83.14 and 80, respectively12 References: 1: Mean, median, and mode review (article) | Khan Academy 2: Mean, Median, and Mode: Measures of Central Tendency - Statistics By Jim

NEW QUESTION 4

Collaborative games are used by a business analyst to identify the research questions to be explored within an analytics system.
Participants are asked to write down a research question on a sticky note, put the notes on the wall,and move them towards related research questions. What type of Collaborative game is being played?

• A. Affinity Map
• B. Fishbowl
• C. People polling
• D. Product Box

Answer: A

Explanation:
An affinity map is a collaborative game that helps participants to group similar ideas or features together. It is useful for identifying research questions that are related to each other and finding common themes or patterns. In this game, participants write down their research questions on sticky notes and place them on the wall. Then, they move the notes around to form clusters of related questions. The clusters can be labeled with a descriptive name or a question that summarizes the theme. An affinity map can help participants to prioritize the most important or relevant research questions and generate insights from the data. https://businessanalystmentor.com/collaborative-games-business-analysis/

NEW QUESTION 5

A call center has requested to review their sales conversion data for the month. The analyst working on this request is trying to identify the chart that will effectively present the data, which includes: the number of leads, the number of calls made, the number of calls completed, the number of customers interested and the number of sales. What chart should the analyst use to show the values across each stage of the pipeline?

• A. Pie chart
• B. Funnel chart
• C. Bar chart
• D. Bullet chart

Answer: B

Explanation:
A funnel chart is a type of chart that shows the values of different stages of a process, such as a sales pipeline, where each stage represents a subset of the previous one. A funnel chart is useful for showing the conversion rate, the drop-off rate, and the potential revenue or profit at each stage12. A funnel chart would be an effective way to present the data requested by the call center, as it would show the number of leads, calls, customers, and sales, as well as the percentage of change between each stage. References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 662: Data Visualization: A Practical Introduction, Kieran Healy, 2018, p. 233.

NEW QUESTION 6

A Human Resource manager recently learned that their competitor reduced employee attrition rates by 20% after implementing personality tests as part of their screening process. Intrigued by the idea, the manager suggests collecting data on personality tests and attrition rates over the next year. The data from this year is then analyzed to explore possible relationships. What type of analytics has the team been asked to perform?

• A. Predictive
• B. Descriptive
• C. Prescriptive
• D. Diagnostic

Answer: B

Explanation:
Descriptive analytics is a type of analytics that summarizes and visualizes the data to provide an overview of what has happened or is happening, such as the attrition rates and the personality test scores of the employees12. The team has been asked to perform descriptive analytics to explore possible relationships between the data variables, without making any predictions or prescriptions for the future. References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 182: Business Analytics: Data Analysis & Decision Making, S. Christian Albright and Wayne L. Winston, 2015, p. 5.

NEW QUESTION 7

An analyst is doing a clinical study on the value of analyte among a large population of healthy people. The analyst is going to use a Gaussian Distribution to share the results. Which of the following represents a Gaussian Distribution? (IMAGE TAKEN)

• A. D
• B. B
• C. A
• D. C

Answer: C

Explanation:
As explained in the previous question, a Gaussian Distribution, also known as a normal distribution, is represented by a symmetrical bell-shaped curve. The mean, median, and mode of the distribution are equal and are at the center of the distribution. This type of distribution is characterized by its mean and standard deviation. The curve is symmetrical around the mean. In the image, the curve labeled A is the only one that matches this description. The other curves are either skewed or irregular.
References: Guide to Business Data Analytics, page 58-59; CBDA Exam Blueprint, page 7; [Introduction to Business Data Analytics: A Practitioner View], page 17.

NEW QUESTION 8

The definition of data elements is different across various data sources. The organization is looking to improve the usability of data across the organization. Which practice would help address this problem?

• A. Data governance
• B. Data quality
• C. Data architecture
• D. Data ethics

Answer: A

Explanation:
Data governance is the practice of establishing and enforcing policies, standards, roles, and responsibilities for the management and use of data across the organization. Data governance helps to address the problem of inconsistent data definitions across various data sources by ensuring that data is properly defined, documented, classified, and aligned with the business objectives and requirements12. References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 292: Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program, John Ladley, 2012, p. 3.

NEW QUESTION 9

The results for a certification exam were revealed in percentage and percentile. The results for one of the attendees was: 75%, 90th percentile. What is the value in sharing the percentile score?

• A. The percentile score provides value by assessing the attendee's score against the average score for that exam
• B. While the exam score is an objective score, the percentile is a relative score that assesses the attendee's score against the highest possible score
• C. By ranking, it provided additional insight on how the attendee performed in comparison to other attendees
• D. The percentile score does not add any additional value in assessing the attendee's performance

Answer: C

Explanation:
The percentile score provides value by ranking the attendee??s score among all the scores of the exam takers. A percentile score of 90 means that the attendee scored higher than 90% of the exam takers, and only 10% scored higher than the attendee. This gives a relative measure of how the attendee performed in comparison to other attendees, and how competitive or exceptional the score is. The percentile score does not depend on the average or the highest possible score of the exam, but only on the distribution of the scores of the exam takers. References:
•Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 4: Interpret and Report Results
•Understanding the Guide to Business Data Analytics, page 9
•What is a Percentile? - Statistics By Jim

NEW QUESTION 10

A marketing department has established an analytics team. The analytics practice is stand- alone and analysts have limited insights into corporate strategy. Which is an expected result for analytics practices operating at the business unit level?

• A. Analytics work will be driven by the organization's business plan
• B. Insights derived from data analysis will be used to guide strategic decisions
• C. The analytics team may conduct analysis that is of minimal value to the organization
• D. The organization will use analytics as a means to obtain a competitive advantage

Answer: C

Explanation:
According to the IIBA® Guide to Business Data Analytics, analytics practices operating at the business unit level are characterized by a lack of alignment with the organization??s strategic objectives, a limited scope of analysis, and a siloed approach to data and insights1. This can result in analytics work that is not relevant, timely, or impactful for the organization as a whole, and that may not address the most critical business problems or opportunities. Therefore, the analytics team may conduct analysis that is of minimal value to the organization, or even detrimental if it leads to suboptimal decisions or actions.
References:1: IIBA® Guide to Business Data Analytics, Chapter 2: Business Data Analytics in Context, page 14-15

NEW QUESTION 11

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

Answer: B

Explanation:
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.
References: Guide to Business Data Analytics, page 54-55; CBDA Exam Blueprint, page 7; [Introduction to Business Data Analytics: A Practitioner View], page 16.

NEW QUESTION 12

A future state data model is created to depict how information will be structured in a proposed solution but the analyst is also interested in modeling how and when data is transformed throughout various processes across the organization.In which model would the analyst find this information?

• A. Process flows
• B. Data flow diagram
• C. Data transformation model
• D. Physical data model

Answer: B

Explanation:
A data flow diagram (DFD) is a graphical representation of how data flows and transforms through a system or process. A DFD shows the sources and destinations of data, the data inputs and outputs, the data transformations and logic, and the data stores and flows. A DFD can help the analyst model howand when data is transformed throughout various processes across the organization, as well as identify potential data quality issues, bottlenecks, and redundancies. A DFD can also complement a future state data model by showing the relationships and dependencies among the data entities and
attributes. References:
✑ Certification in Business Data Analytics (IIBA ® - CBDA), IIBA, accessed on January 20, 2024.
✑ Business Data Analytics Certification - CBDA Competencies | IIBA®, IIBA, accessed on January 20, 2024.
✑ Guide to Business Data Analytics, IIBA, 2020, p. 19-20.
✑ Data Flow Diagram - Everything You Need to Know About DFD, Visual Paradigm, accessed on January 20, 2024.

NEW QUESTION 13

The analytics team has been asked to assess sales data from their company's website with the hopes of providing insights to help increase online sales. It's the first time the team is looking at this specific data and they are concerned about the quality of data that has been captured. They decide to use the following approach as the next step:

• A. Trend Analysis
• B. Classification analysis
• C. Data Analysis
• D. Exploratory analysis

Answer: D

Explanation:
Exploratory analysis is the approach that the analytics team should use as the next step, because it is a technique that allows them to examine the quality, structure, and characteristics of the data, without making any assumptions or hypotheses. Exploratory analysis can help the team identify any issues or anomalies in the data, such as missing values, outliers, or errors, and decide how to handle them. Exploratory analysis can also help the team discover any patterns, trends, or relationships in the data, and generate new research questions or hypotheses for further analysis. References:
•Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 3: Analyze Data
•Understanding the Guide to Business Data Analytics, page 16
•CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA®, page 8, CBDA Exam Sample Questions and Self-Assessment, Question 8

NEW QUESTION 14

The research study is complete, the data has been analyzed and the team has created the necessary high impact visuals.The business analysis professional urges the team to:

• A. Present the results to stakeholders
• B. Validate regression analysis
• C. Curate the data
• D. Develop the narrative

Answer: D

Explanation:
Developing the narrative is the process of creating a clear, concise, and compelling story that communicates the key insights, findings, and recommendations from the data analysis to the stakeholders1. Developing the narrative is an important step after completing the research study, the data analysis, and the high impact visuals, as it helps to bridge the gap between the data and the decision-making, to engage and persuade the audience, and to drive action and change2. Developing the narrative involves defining the purpose, audience, and message of the story, choosing the best format and medium to deliver the story, and using effective storytelling techniques, such as structure, context, emotion, and call to action3.
Presenting the results to stakeholders is the process of delivering the data story to the intended audience, using the appropriate communication channels, methods, and tools4. Presenting the results to stakeholders is a subsequent step after developing the narrative, as it requires a well-crafted and well-prepared data story to be effective and impactful. Presenting the results to stakeholders involves planning and rehearsing the presentation, adapting to the feedback and questions, and evaluating the outcomes and impacts of the presentation5.
Validating regression analysis is the process of checking the assumptions, accuracy, and suitability of a statistical model that estimates the relationship between one or more independent variables and a dependent variable. Validating regression analysis is a part of the data analysis step, not a step after completing the data analysis. Validating regression analysis involves testing the significance, fit, and residuals of the model, and comparing the model with alternative models or methods.
Curating the data is the process of organizing, annotating, and preserving the data for future use, reuse, or sharing. Curating the data is a part of the data management step, not a step after completing the data analysis. Curating the data involves applying the data policies, standards, and best practices of the organization, and ensuring the quality, integrity, security, and accessibility of the data.
References:1: Guide to Business Data Analytics, IIBA, 2020, p. 572: Introduction to Business Data Analytics: An Organizational View, IIBA, 2019, p. 153: Data Storytelling: The Definitive Guide, Tableau, 4: Guide to Business Data Analytics, IIBA, 2020, p. 585: Introduction to Business Data Analytics: A Practitioner View, IIBA, 2019, p. 27. : Guide to Business Data Analytics, IIBA, 2020, p. 55. : Data Analysis: The Definitive Guide, Tableau,. : Guide to Business Data Analytics, IIBA, 2020, p. 45. : Data Management: The Definitive Guide, Tableau, . : Data Storytelling: The Definitive Guide, Tableau, . : Guide to Business Data Analytics, IIBA, 2020, p. 57. : Introduction to Business Data Analytics: An Organizational View, IIBA, 2019, p. 15. : Data Storytelling: The Definitive Guide, Tableau, .
: Guide to Business Data Analytics, IIBA, 2020, p. 58. : Introduction to Business Data Analytics: A Practitioner View, IIBA, 2019, p. 27. : Guide to Business Data Analytics, IIBA, 2020, p. 55. : Data Analysis: The Definitive Guide, Tableau, . : Guide to Business Data Analytics, IIBA, 2020, p. 45. : Data Management: The Definitive Guide, Tableau, .

NEW QUESTION 15

The marketing department for a major restaurant chain is interested in testing a Kids Eat Free campaign to determine if it will help to increase sales. They are interested in piloting the campaign to determine which day of the week will improve sales the most.
The campaign is launched across 7 cities with each city promoting a different day of the week. The sales data is collected and provided to a team for analysis. What concern might the analytics team have regarding data quality across cities?

• A. Normality
• B. Heteroskedacity
• C. Linearity
• D. Variation

Answer: D

Explanation:
Variation is the degree to which the data values differ from each other or from a central tendency measure, such as the mean or median. Variation can affect the data quality across cities, as it can indicate the presence of outliers, errors, noise, or inconsistency in the data collection or processing methods. Variation can also influence the statistical analysis and interpretation of the results, as it can affect the significance, confidence, and validity of the findings12. References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 302: Statistics for Business and Economics, David R. Anderson et al., 2014, p. 83.

NEW QUESTION 16
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