IIBA CBDA Online Practice Questions and Exam Preparation

IIBA CBDA Online Questions & Answers

• Question 1:

  A real estate broker is tracking monthly sales between two of its teams. The results have been visualized using a Treemap chart. What is the advantage of using a Treemap chart, over a Sunburst chart to visualize the results?

  A. With its colour scheme, it is easy to compare the variables within a Treemap
  B. With its rectangles and straight lines, a Treemap is optimized to include more
  C. A Treemap is meant to represent a hierarchical result set as opposed to a Sunburst chart
  D. A Treemap shows all the hierarchical levels of data as opposed to a Sunburst chart
  B. With its rectangles and straight lines, a Treemap is optimized to include more

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  explanation:

  Explanation/Reference:

  A Treemap chart is a type of chart that displays hierarchical data as a set of nested rectangles, where the size and color of each rectangle represent a quantitative value and a categorical variable, respectively. A Sunburst chart is a type of chart that displays hierarchical data as a set of concentric circles, where the size and color of each slice represent a quantitative value and a categorical variable, respectively. Both charts are useful for visualizing hierarchical data structures, but they have different advantages and disadvantages. One advantage of using a Treemap chart over a Sunburst chart is that a Treemap chart is optimized to include more data points, as it uses a Cartesian coordinate system that fills the entire rectangular space of the chart area, whereas a Sunburst chart uses a polar coordinate system that leaves empty spaces in the corners of the chart area. This means that a Treemap chart can display more levels of hierarchy, more categories, and more details than a Sunburst chart, without compromising readability or clarity. Therefore, the correct answer is B, as a Treemap chart is optimized to include more data than a Sunburst chart.

• Question 2:

  The Vice President at a commercial goods manufacturing company wants to create annual objectives for the team based on the company's latest strategic goals. The Vice President has reached out to the business analytics team for data analysis that will help build SMART objectives. What type of analytics will help with creating these objectives?

  A. Descriptive
  B. Diagnostic
  C. Descriptive and Diagnostic
  D. Descriptive and Predictive
  D. Descriptive and Predictive

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  explanation:

  Explanation/Reference:

  Descriptive and predictive analytics are types of analytics that can help with creating SMART objectives. SMART stands for Specific, Measurable, Achievable, Relevant, and Time-bound, which are criteria for setting effective and realistic goals1. Descriptive analytics is the type of analytics that summarizes what has happened in the past using data, such as historical trends, patterns, or performance2. Descriptive analytics can help with creating SMART objectives by providing a baseline, benchmark, or context for the current situation and the desired outcomes. Predictive analytics is the type of analytics that forecasts what is likely to happen in the future using data, such as statistical models, machine learning, or artificial intelligence3. Predictive analytics can help with creating SMART objectives by providing a projection, estimation, or scenario for the future situation and the expected results.

  Diagnostic and prescriptive analytics are other types of analytics that are not as helpful with creating SMART objectives. Diagnostic analytics is the type of analytics that explains why something has happened in the past using data, such as root cause analysis, correlation analysis, or hypothesis testing. Diagnostic analytics can help with understanding the causes and effects of past events, but it does not provide guidance or direction for setting future goals. Prescriptive analytics is the type of analytics that recommends what should be done in the future using data, such as optimization, simulation, or decision analysis. Prescriptive analytics can help with suggesting the best actions or alternatives for achieving future goals, but it does not define or measure the goals themselves.

• Question 3:

  An analytics team completed their research to determine why customers are abandoning items in their online shopping cart. The team suggests improvements to the website to address the problem. The Director of Sales proclaims that the current website is fine and indicates that the problem materialized when the company increased its shipping rates. The solution proposed by the team seems misaligned. What has gone wrong?

  A. This scenario cannot be addressed with analytics
  B. The team has not agreed on the root cause of the problem
  C. The team did not agree on the business problem
  D. An insufficient amount of planning was performed
  C. The team did not agree on the business problem

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  explanation:

  Explanation/Reference:

  Agreeing on the business problem is the first and most critical step in any analytics project, as it defines the scope, purpose, and objectives of the analysis, and aligns the expectations and interests of the stakeholders1. Agreeing on the business problem involves identifying the problem statement, the problem owner, the problem context, the problem impact, and the problem criteria2. If the team did not agree on the business problem, the solution proposed by the team may seem misaligned with the actual needs, preferences, or assumptions of the decision makers, and may not address the root cause or the main drivers of the problem. In this scenario, the team and the Director of Sales may have different views on what the business problem is, why it is important, and how it should be solved.

  The other options are not correct explanations of what has gone wrong. This scenario can be addressed with analytics, as it involves using data to understand customer behavior, identify factors influencing cart abandonment, and recommend improvements to the website or the pricing strategy. The team may or may not have agreed on the root cause of the problem, but that is not the main issue, as the root cause analysis is a part of the data analysis step, not the problem definition step. The team may or may not have performed an insufficient amount of planning, but that is not the main issue, as the planning process is a subsequent step after the problem definition step, and it depends on the clarity and agreement of the business problem.

• Question 4:

  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?

  A. Data validity
  B. Data privacy
  C. Data reliability
  D. Data reproducibility
  A. Data validity

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  explanation:

  Explanation/Reference:

  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.

• Question 5:

  An analytics team is discussing ways to improve company performance. Before identifying a set of research questions to analyze, they identify the need to understand the current company strategy and performance. The business analyst suggests using the Balanced Scorecard technique to guide this discussion. In which dimension of the matrix would the team be discussing metrics for changing and improving?

  A. Learning and Growth
  B. Customer
  C. Financial
  D. Internal Business Process
  A. Learning and Growth

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  explanation:

  Explanation/Reference:

  According to the Introduction to Business Data Analytics: An Organizational View, the Balanced Scorecard technique is a strategic management tool that helps organizations align their vision, mission, and goals with their performance measures. The Balanced Scorecard consists of four dimensions: financial, customer, internal business process, and learning and growth. Each dimension has a set of objectives, measures, targets, and initiatives that reflect the organization's strategy and value proposition. The learning and growth dimension focuses on the metrics for changing and improving the organization'scapabilities, such as employee skills, knowledge, innovation, and culture. The learning and growth dimension supports the other three dimensions by providing the necessary resources and competencies to achieve the desired outcomes.

• Question 6:

  A brainstorming session is conducted to identify the research questions to be explored within an analytics project. During the brainstorming activity which of the following should happen?

  A. The number of questions generated should be limited to contain scope
  B. Participants should make sure the questions are unique and realistic
  C. Participants should add questions as they come to mind without restriction on time limit
  D. Participants should avoid critiquing suggested questions raised by the group
  D. Participants should avoid critiquing suggested questions raised by the group

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  explanation:

  Explanation/Reference:

  According to the Guide to Business Data Analytics, brainstorming is a technique used to generate a large number of ideas or questions in a short period of time1. The purpose of brainstorming is to encourage creativity and divergent thinking, not to evaluate or judge the ideas or questions. Therefore, participants should avoid critiquing suggested questions raised by the group, as this could inhibit the flow of ideas and discourage participation. The other options are not consistent with the principles of brainstorming, as they could limit the quantity or quality of the questions generated.

• Question 7:

  As the organization looks to advance its analytics practices, the topic of provisioning access to executive dashboards and visualizations is under discussion. Establishing standards and implementing role based logins to executive dashboards will address:

  A. Data management
  B. Data security
  C. Data governance
  D. Content management
  B. Data security

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  explanation:

  Explanation/Reference:

  According to the Guide to Business Data Analytics, data security is the protection of data from unauthorized access, use, modification, or destruction. Data security includes the policies, procedures, and technologies that ensure the confidentiality, integrity, and availability of data. Data security is an important aspect of data management, which is the planning, execution, and oversight of the data lifecycle. Data security is also related to data governance, which is the establishment and enforcement of rules, roles, and responsibilities for data quality, access, and usage. Data security is not the same as content management, which is the creation, storage, distribution, and maintenance of digital content.

  One of the ways to enhance data security is to provision access to executive dashboards and visualizations based on the roles and permissions of the users. This can help prevent unauthorized or inappropriate access to sensitive or confidential data, as well as ensure compliance with data privacy and ethical standards. By establishing standards and implementing role based logins to executive dashboards, the organization can address the data security needs of its analytics practices.

• Question 8:

  After completing their data analysis, an analyst is drawing out the results, explaining the methods and processes used, and identifying any limitations or weaknesses in the data or methods applied. While performing these steps, which recommended practice would the analyst apply?

  A. Use exploratory analysis to determine the best mathematical method to use
  B. Understand the communication needs of stakeholders
  C. Let the data drive the conclusions and the insights reached
  D. Learn a variety of visualization techniques for effective communications
  B. Understand the communication needs of stakeholders

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  explanation:

  Explanation/Reference:

  According to the IIBA?Guide to Business Data Analytics, communication is a key skill for analysts, as it involves conveying the results, methods, and limitations of the data analysis to various stakeholders in a clear, concise, and meaningful way. To communicate effectively, analysts need to understand the communication needs of stakeholders, such as their level of interest, knowledge, and influence, their preferred format and frequency of communication, and their expectations and objectives. Byunderstanding the communication needs of stakeholders, analysts can tailor their messages, choose the appropriate language and tone, and select the most suitable communication channels and media. Therefore, the correct answer is B, as understanding the communication needs of stakeholders is a recommended practice for analysts while performing the steps of drawing out the results, explaining the methods and processes used, and identifying any limitations or weaknesses in the data or methods applied.

• Question 9:

  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?

  A. Evidenced-based decision making
  B. Expert judgement and experience
  C. Correlations identified through artificial intelligence
  D. Letting the data tell the story
  B. Expert judgement and experience

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  explanation:

  Explanation/Reference:

  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 10:

  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?

  A. Document analysis
  B. Journey map
  C. Current state assessment
  D. Interface analysis
  B. Journey map

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  explanation:

  Explanation/Reference:

  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.