IIBA IIBA Certifications CBDA Questions & Answers

• Question 21:

  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

  Correct Answer: C

  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.

• Question 22:

  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

  Correct Answer: B

  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.

• Question 23:

  A financial institution is interested in leveraging analytics to address a recent surge in credit card fraud. The company has decided to invest in streaming analytics to obtain instant access to real-time data to stop fraudulent behavior before it occurs. Which practice will help the financial institution integrate the data as it is collected?

  A. Data quality

  B. Data management

  C. Data security

  D. Data architecture

  Correct Answer: D

  Data architecture is the practice of designing and implementing the structures, models, standards, and processes that enable data integration, storage, and consumption. Data architecture is essential for streaming analytics, as it defines how data is collected, processed, and delivered in real time from multiple sources. Data architecture helps the financial institution integrate the data as it is collected by ensuring data compatibility, consistency, and quality across the streaming pipeline. Data architecture also supports data security, scalability, and performance for streaming analytics.

• Question 24:

  A merger has been completed between two telecommunication companies and the analytic practices from both organizations are being joined. The newly formed analytics department will create a task force of data experts to combine the data from both companies into a structure usable for future analytics initiatives. Which of the following activities would provide a high level understanding about any potential data issues that might be encountered when merging sources?

  A. Data conversion

  B. Data cleansing

  C. Data migration

  D. Data profiling

  Correct Answer: D

  According to the Guide to Business Data Analytics, data profiling is a technique that analyzes the structure, content, and quality of data sources. Data profiling can help identify data issues such as missing values, outliers, inconsistencies, duplicates, and errors. Data profiling can also provide information about the data types, formats, ranges, distributions, and relationships of data elements. Data profiling can help prepare data for data conversion, data cleansing, and data migration by providing a high level understanding of the current state of data and the potential challenges and risks involved in transforming and integrating data from different sources.

• Question 25:

  What is the relationship between a Customer entity and an Order entity, where a customer entry will be present in the Customer entity regardless of whether an order was made?

  A. zero-to-one

  B. many-to-many

  C. zero-to-many

  D. one-to-one

  Correct Answer: C

  A zero-to-many relationship between two entities means that one instance of the first entity can be associated with zero or more instances of the second entity, and one instance of the second entity can be associated with only one instance of the first entity1. In this case, a customer entry will be present in the Customer entity regardless of whether an order was made, which means that a customer can have zero or more orders, but an order can only belong to one customer. Therefore, the relationship between Customer and Order is zero-to-many.

• Question 26:

  A business analyst is conducting a series of interviews to understand the research questions that will be explored within a new analytics project. Which of the following is true about interviews?

  A. Planned interviews are less effective than unplanned

  B. Interviews must be structured to be effective

  C. Goals for the interview should be clearly articulated

  D. Interviews should only be conducted with one interviewee

  Correct Answer: C

  Interviews are a technique to elicit information from stakeholders and subject matter experts. Interviews can be planned or unplanned, structured or unstructured, depending on the context and purpose of the interview. However, regardless of the type of interview, it is important to have clear goals for the interview, such as what information is needed, what questions will be asked, and how the information will be used. Having clear goals for the interview helps the interviewer to prepare, conduct, and follow up the interview effectively, and also helps the interviewee to understand the expectations and provide relevant and accurate information.

• Question 27:

  A grocery store chain has requested help in determining how customer preferences are changing with regards to home delivery. An analytics team has completed researching the number of online orders received requesting home delivery versus in-store pickup. The business analyst has selected a model to enable a quick comparison between curbside pick-up, in-store pickup, and home delivery for the last 3 years.Which model has the business analyst chosen?

  A. Pie chart

  B. Funnel chart

  C. Scatter plot

  D. Bar chart

  Correct Answer: D

  A bar chart is a graphical representation of data that uses rectangular bars of different heights or lengths to show the values of one or more variables1. A bar chart is suitable for comparing the number of online orders received requesting different types of delivery options for the last 3 years, as it can show the frequency or proportion of each category across time. A bar chart can also help identify trends, patterns, or outliers in the data2.

  A pie chart is a circular chart that shows the relative sizes of data points in a whole by using different-sized and colored slices3. A pie chart is not suitable for comparing the number of online orders received requesting different types of delivery options for the last 3 years, as it can only show the distribution of one variable at a time, and it does not show the changes over time. A pie chart can also be misleading or confusing if there are too many categories or if the slices are too similar in size4.

  A funnel chart is a type of chart that shows the stages of a process and the amount of data that passes through each stage5. A funnel chart is not suitable for comparing the number of online orders received requesting different types of delivery options for the last 3 years, as it does not show the categories of delivery options, but rather the progression of customers through a sales or marketing funnel. A funnel chart can help visualize the conversion rates, drop-off rates, or bottlenecks in a process6.

  A scatter plot is a type of chart that shows the relationship between two numerical variables by using dots to represent the values of each pair of data points. A scatter plot is not suitable for comparing the number of online orders received requesting different types of delivery options for the last 3 years, as it does not show the categories of delivery options, but rather the correlation or association between two continuous variables. A scatter plot can help identify the direction, strength, and shape of the relationship, as well as any outliers or clusters in the data.

• Question 28:

  A supermarket chain wants to improve supplier relations. One of the targets to track and help achieve this goal is to improve the average transaction time per order by 10%.From a SMART target perspective, what is missing?

  A. is not attainable as weather conditions can slow down order times

  B. S ?should provide a target for each supplier

  C. Ris not relevant to the goal as supplier relations is only dependent on quality of deliveries

  D. TThere is no mention of the time-frame by which this target must be met

  Correct Answer: D

  SMART is an acronym that stands for Specific, Measurable, Achievable, Relevant, and Time-bound, which are criteria for setting effective and realistic goals1. From a SMART target perspective, what is missing in this scenario is the time-frame by which the target must be met. A time-bound target specifies the deadline or the duration for achieving the target, which helps to create a sense of urgency, motivation, and accountability2. Without a time-frame, the target is vague and indefinite, and it is difficult to monitor and evaluate the progress and the results. For example, a time-bound target could be to improve the average transaction time per order by 10% within the next six months.

  The other options are not correct explanations of what is missing. The target is attainable, as it is realistic and feasible, and it does not depend on factors that are beyond the control of the organization, such as weather conditions. The target is specific, as it provides a clear and precise description of what needs to be achieved, and it does not need to provide a target for each supplier, as that would make the target too complex and cumbersome. The target is relevant, as it is aligned with the goal of improving supplier relations, and it does not assume that supplier relations is only dependent on quality of deliveries, as transaction time is also an important factor that affects the efficiency, satisfaction, and trust of the suppliers.

• Question 29:

  An operations manager for a new hotel is in need of determining the optimum number of vans to purchase to shuttle guests to/from the airport. It will be necessary to determine the most efficient routes and schedule to follow to ensure guests do not experience excessive delays. Which business analytics technique would lend itself to supporting these types of business decisions?

  A. Linear programming

  B. Factor analysis

  C. Regression

  D. K-means Clustering

  Correct Answer: A

  Linear programming is a business analytics technique that can lend itself to supporting these types of business decisions. Linear programming is a mathematical method that optimizes the allocation of limited resources to achieve a desired objective, subject to a set of constraints1. Linear programming can help the operations manager to determine the optimum number of vans to purchase, the most efficient routes and schedule to follow, and the minimum cost or time to shuttle guests to/from the airport, by formulating a linear objective function and a system of linear inequalities that represent the relevant variables, parameters, and restrictions2.

  The other options are not correct business analytics techniques for these types of business decisions. Factor analysis is a statistical method that reduces the dimensionality of a large set of correlated variables into a smaller set of uncorrelated factors that explain the underlying structure or patterns of the data3. Factor analysis can help the operations manager to identify the key factors that influence the guest satisfaction or loyalty, but it cannot help to optimize the resource allocation or efficiency. Regression is a statistical method that estimates the relationship between one or more independent variables and a dependent variable. Regression can help the operations manager to predict the demand or revenue of the hotel based on the variables such as season, price, or location, but it cannot help to optimize the resource allocation or efficiency. K-means clustering is a machine learning method that partitions a set of data points into a predefined number of clusters based on the similarity or distance between the data points. K-means clustering can help the operations manager to segment the guests into different groups based on their characteristics or preferences, but it cannot help to optimize the resource allocation or efficiency.

• Question 30:

  A small business has recently launched their website and wants to understand how the website is being used. In particular, there is interest in identifying which areas of each page receive the most attention. The analyst has decided to communicate this information by displaying the top pages overlaid with colours denoting the volume of clicks.What type of visualization technique is being used here?

  A. Surface chart

  B. Heatmap

  C. Treemap

  D. Scatter chart

  Correct Answer: B

  According to the Guide to Business Data Analytics, a heatmap is a type of visualization technique that uses colours to represent the values of a variable across a two-dimensional space. A heatmap can help reveal patterns, trends, and outliers in the data, as well as show the relative importance or intensity of different areas. In this situation, the analyst has decided to communicate the information about the website usage by displaying the top pages overlaid with colours denoting the volume of clicks. This is a heatmap, as it uses colours to show the distribution and magnitude of clicks across the web pages.