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NEW QUESTION # 28
An insurance company has seen an upward trend in winter-related accidents over the past three years. The company has just completed an analytics study to better understand the primary reasons for these accidents and assess how many of the drivers were using winter tires. This analysis will help the company decide how to move forward with drivers not taking precautionary measures during winter. What type of analysis will help in determining the primary reasons and percentage of those drivers with winter tires?
- A. Prescriptive
- B. Descriptive
- C. Descriptive and Predictive
- D. Descriptive and Diagnostic
Answer: D
Explanation:
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 trend of winter-related accidents over the past three years, or the percentage of drivers using winter tires12. Diagnostic analytics is a type of analytics that explores and analyzes the data to understand why something has happened or is happening, such as the primary reasons for these accidents, or the factors that influence the drivers' decisions13. To answer the question, both descriptive and diagnostic analytics would be needed to provide the relevant information and insights for the company.
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. 53: Data Science for Business, Foster Provost and Tom Fawcett, 2013, p. 13.
NEW QUESTION # 29
A government agency is conducting a study on the performance of 12th grade students' in mathematics across the country. In particular, they want to understand if there is a relationship between intelligence and scores, as well as the difference in performance between various locations. Which combination of inferential statistics procedures should be used?
- A. Frequency distribution, time-series
- B. Mean, median
- C. Range, standard deviation
- D. Correlation co-efficient, analysis of variance
Answer: D
Explanation:
Explanation
A correlation co-efficient is a measure of the strength and direction of the linear relationship between two variables, such as intelligence and scores. A correlation co-efficient can range from -1 to 1, where -1 indicates a perfect negative relationship, 0 indicates no relationship, and 1 indicates a perfect positive relationship12. An analysis of variance (ANOVA) is a procedure that tests whether the means of two or more groups are significantly different from each other, such as the performance of students across various locations. ANOVA can compare the variation within each group and the variation between groups to determine if there is a statistically significant difference among the group means34. References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 582: Statistics for Business and Economics, David R. Anderson et al., 2014, p. 7133: Guide to Business Data Analytics, IIBA, 2020, p. 594: Statistics for Business and Economics, David R. Anderson et al.,
2014, p. 849.
NEW QUESTION # 30
A software company launched a new product in late 2016. The product manager is reviewing a Box and Whisker plot used to compare year-over-year sales, from 2017 to 2018. What is the conclusion he can make from this chart?
- A. 2018 minimum and maximum sales are higher than 2017, and the 2018 quartile results are higher than 2017 quartile results
- B. 2018 minimum and maximum sales are higher than 2017, and the 2018 1st quartile is higher than 2017 median result
- C. 2017 minimum and maximum sales are higher than 2018, and the 2017 median result is higher than the 2018 median result
- D. 2017 minimum and maximum sales are higher than 2018, but the 2017 median result is lower than 2018 1st quartile result
Answer: B
NEW QUESTION # 31
The analytics team has been asked to determine if the organization should launch their highest revenue generating product into the North American market. To date, this has only been available in Eastern Europe.
To answer this, the team formulates several research questions, including:
- A. What product launch related costs can we expect?
- B. Why does management need to know this?
- C. How much revenue does the product generate in Eastern Europe?
- D. Do existing customers really like the product?
Answer: D
Explanation:
Explanation
One of the steps in identifying the research questions for business data analytics is to assess the feasibility and desirability of the proposed solution or change1. This involves understanding the needs, preferences, and satisfaction of the existing and potential customers. Therefore, asking whether the existing customers really like the product is a relevant research question for the analytics team. References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 22.
NEW QUESTION # 32
A large telecommunications company wants to increase their Average Revenue Per User per month by 5%, by end of year, to increase revenue in a highly competitive market. From a SMART target perspective, what is missing?
- A. S - There is no mention of which product group/line the target pertains to
- B. R - Since competition is high, focus should be on increasing customer base and not on ARPU
- C. T - The increase should be seen sooner
- D. A - It is too easy of a target to attain
Answer: A
Explanation:
Explanation
A SMART target is one that is specific, measurable, achievable, relevant, and time-bound1. The target of increasing the Average Revenue Per User (ARPU) per month by 5%, by end of year, to increase revenue in a highly competitive market is missing the specificity criterion, as it does not mention which product group or line the target applies to. The target should be more specific and clear about the scope and context of the desired outcome, such as which segment, region, or service the target relates to23. References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 192: SMART Goals: How to Make Your Goals Achievable, MindTools, 2021, 13: How to Set SMART Marketing Goals, CoSchedule, 2021, 2.
NEW QUESTION # 33
Which attributes from the Order entity will need to be normalized to avoid redundancies?
. Orderld
. OrderDate
. Itemld
. ItemName
. Quantity
. ItemPrice
- A. Item Name
Quantity - B. ItemName
ItemPrice - C. OrderDate
ItemPrice - D. OrderDate
ItemName
Answer: B
Explanation:
Explanation
The attributes ItemName and ItemPrice need to be normalized to avoid redundancies because they depend on the attribute ItemId, which is not part of the primary key of the Order entity. This is a case of partial dependency, which violates the second normal form (2NF) of database normalization. To achieve 2NF, the Order entity should be split into two entities: Order and Item, where Item contains the attributes ItemId, ItemName, and ItemPrice, and Order contains the attributes OrderId, OrderDate, ItemId, and Quantity. This way, the ItemName and ItemPrice are stored only once for each ItemId, and the Order entity references them through a foreign key12 References: 1: Balancing Data Integrity and Performance: Normalization vs ... 2:
Normalization Process in DBMS - GeeksforGeeks
NEW QUESTION # 34
A research marketer is interested in collecting information about the spending habits of families in North America. Concerned about the volume of data required to conduct the research, they choose to use sampling.
The dataset is sourced using all credit card transactions from a leading North American credit card company for Quarter 1 of the prior year. The sample used is:
- A. Biased
- B. Too large to be helpful
- C. Not relevant
- D. Statistically representative
Answer: A
Explanation:
Explanation
The sample used in this case is biased, meaning that it is not representative of the population of interest. The population of interest is the families in North America, but the sample is drawn from only one source of data:
the credit card transactions from a leading North American credit card company. This sample excludes the families who do not use credit cards, or who use other credit card companies, or who use other payment methods. Therefore, the sample is not random or fair, and it may introduce sampling bias into the research results12 References: 1: Sampling Methods | Types, Techniques & Examples 2: Sampling Bias - an overview | ScienceDirect Topics
NEW QUESTION # 35
The interplay between enterprise systems and data analytics can be envisioned at various layers. The layer that connects the business processes to data analytics is the:
- A. information layer
- B. technical layer
- C. infrastructure layer
- D. physical layer
Answer: A
Explanation:
Explanation
The information layer is the layer that connects the business processes to data analytics. It consists of the data models, data quality, data governance, and data security that enable the data to be accessed, analyzed, and transformed into insights. The information layer also supports the communication and collaboration among the stakeholders involved in the data analytics process. The other layers are the physical layer, which deals with the hardware and software components of the data infrastructure; the technical layer, which handles the data integration, data storage, data processing, and data analysis techniques; and the infrastructure layer, which provides the network, cloud, and security services for the data environment12 References: 1: Data and Analytics (D&A) - Gartner 2: Enterprise Data Analytics - SelectHub
NEW QUESTION # 36
The team has completed their analysis on a vast amount of collected data and agree on their recommendations for action.
However, they are having difficulty in developing the appropriate messages to support their recommendations.
The business analysis professional suggests which technique to assist the team?
- A. Simulation
- B. Storyboarding
- C. T-Testing
- D. Visioning
Answer: B
Explanation:
Explanation
Storyboarding is a technique that helps the team to develop the appropriate messages to support their recommendations by creating a visual sequence of the main points, evidence, and actions. Storyboarding helps the team to organize their thoughts, identify gaps, and communicate their findings in a clear and compelling way12 References: 1: Developing Key Messages for Effective Communication - MSKTC 2: 11 Ways Highly Successful Leaders Support Their Team - Redbooth
NEW QUESTION # 37
An analyst at a supermarket chain has been asked to extract data from multiple data sources to complete a study on customer spending habits. The analyst is going to query data from various databases. Which statement is true about database querying?
- A. Querying can be used to create predictive data models
- B. A querying language is independent of the type of database being used
- C. Querying is a structured way of searching, manipulating and managing data
- D. Irrespective of the querying language used, data results retrieved are always in a tabular format
Answer: C
Explanation:
Explanation
Querying is a technique that allows analysts to access, filter, join, aggregate, and transform data from various databases using a specific syntax and logic1. Querying can be used for different purposes, such as data exploration, data preparation, data analysis, and data visualization2. Querying is not limited to creating predictive data models, nor does it always produce tabular results. Moreover, querying languages may vary depending on the type and structure of the database, such as relational, hierarchical, or document-based3.
References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 552: Data Analysis Using SQL and Excel, Gordon S. Linoff, 2016, p. 33: Database Systems: Design, Implementation, and Management, Carlos Coronel and Steven Morris, 2019, p. 17.
NEW QUESTION # 38
While creating a dataset for analysis, the analyst reviews the data collected and finds a large percentage of records are missing values. Which activity would the analyst perform in order to use this dataset?
- A. Clustering
- B. Scale validation
- C. Weighting
- D. Factor analysis
Answer: C
Explanation:
Explanation
Weighting is a technique that assigns different values or weights to different records or variables in a dataset, based on their importance or relevance. Weighting can be used to handle missing values by giving them a lower weight or imputing them with a weighted average of other values. Weighting can also help to adjust for sampling bias or non-response bias in the data collection process. References:
*Understanding the Guide to Business Data Analytics, page 16
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 3:
Analyze Data
*CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA®, page 8, CBDA Exam Sample Questions and Self-Assessment, Question 4
NEW QUESTION # 39
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. People polling
- B. Fishbowl
- C. Product Box
- D. Affinity Map
Answer: D
Explanation:
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 # 40
A dataset contains 10 measures of workplace sustainability. The analytics team is in need of producing a single score of sustainability. Which of the following techniques if used would achieve this objective?
- A. Linkage algorithms
- B. Factor analysis
- C. K means clustering
- D. Logistic regression
Answer: B
Explanation:
Explanation
Factor analysis is the technique that, if used, would achieve the objective of producing a single score of sustainability, because it is a technique that reduces the dimensionality of a data set by identifying the underlying factors or latent variables that explain the variation and correlation among the observed variables.
Factor analysis can help the analytics team combine the 10 measures of workplace sustainability into a smaller number of factors, and then derive a composite score of sustainability based on the factor loadings and weights. Factor analysis can also help the analytics team simplify and interpret the data, and identify the key drivers of sustainability. References:
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 3:
Analyze Data
*Understanding the Guide to Business Data Analytics, page 17
*Business Data Analytics (IIBA®-CBDA Exam preparation) | Udemy, Section 3: Analyze Data, Lecture 15:
Factor Analysis
NEW QUESTION # 41
A professor at a university has received a few complaints of the exams being too difficult. The professor is looking at exam performance results over the past 5 years to understand the normal tendency and outliers.
Which chart should the professor use?
- A. Pie chart
- B. Scatterplot
- C. Line
- D. Sunburst
Answer: B
Explanation:
Explanation
A scatterplot is a type of chart that shows the relationship between two variables by plotting data points on a two-dimensional plane. A scatterplot can help the professor to understand the normal tendency and outliers of exam performance results over the past 5 years by displaying the distribution, trend, and correlation of the data. For example, the professor can use the x-axis to represent the year and the y-axis to represent the exam score, and see how the scores vary over time and across different exams. Outliers can be identified as data points that are far away from the main cluster or the line of best fit12 References: 1: Scatter Plot - Statistics How To 2: Scatterplots - IIBA BABOK Guide v3
NEW QUESTION # 42
While sourcing data, an analyst runs into a situation where different business units are using different names to refer to the same data element. This lack of standardization is resulting in confusion and additional time required to properly prepare data for analysis. Which practice, if implemented would address this situation and mature the organization's business analytics practice?
- A. Meta data management
- B. Data warehousing
- C. Data quality management
- D. Database operations management
Answer: A
Explanation:
Explanation
Meta data management is the practice that, if implemented, would address the situation and mature the organization's business analytics practice, because it is a technique that involves defining, documenting, and maintaining the information about the data elements, such as their names, definitions, formats, sources, and relationships. Meta data management can help the analyst resolve the inconsistencies and ambiguities in the data element names, and ensure that the data is standardized, consistent, and understandable across different business units. Meta data management can also help the analyst improve the data quality, accessibility, and usability for the analysis. References:
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 2: Source Data
*Guide to Business Data Analytics - Iiba - Google Books, page 14
*Business Data Analytics (IIBA®-CBDA Exam preparation) | Udemy, Section 2: Source Data, Lecture 8:
Meta Data Management
NEW QUESTION # 43
An organization's customers are categorized based on the amount of purchases completed over the last 12 months. The analytics team would like to ensure the accuracy of their survey results and decide to randomly select 500 customers to participate in a survey from this large pool of customers. This is an example of:
- A. Snowball sampling
- B. Purposive sampling
- C. Quota sampling
- D. Stratified sampling
Answer: D
Explanation:
Explanation
Stratified sampling is a technique that divides the population into homogeneous subgroups (strata) based on a relevant characteristic, such as the amount of purchases, and then randomly selects a proportional number of elements from each subgroup to form the sample. Stratified sampling ensures that the sample is representative of the population and reduces the sampling error and bias12. References: 1: Guide to Business Data Analytics, IIBA, 2020, p. 312: Statistics for Business and Economics, David R. Anderson et al., 2014, p. 262.
NEW QUESTION # 44
The analytics team is assessing the results of their analysis. They are surprised to find that their data indicates two events seem to be strongly related even though the general belief in the organization is that they are independent of each other. Knowing that this information will be used for decision making, they are concerned about presenting this data. At an impasse, the business analysis professional reminds them that the data can be presented as long as the team has:
- A. Confidence that the correlation will reliably occur in the future and the risk of acting on this is low
- B. Followed all rules for data analysis endorsed as organizational standards so the risk of acting on this is low
- C. The ability to rerun the data analysis and the results are the same thereby minimizing the risk of acting on this
- D. Review the results with management ahead of time and highlight any potential risk of using this data
Answer: C
Explanation:
Explanation
The ability to rerun the data analysis and the results are the same is the condition that the team should have before presenting the data, because it is a technique that ensures the validity, reliability, and reproducibility of the data analysis. By rerunning the data analysis, the team can verify that the results are consistent and not affected by random errors, biases, or anomalies. The team can also confirm that the data analysis process is well-documented, transparent, and traceable, and that the results can be replicated by other analysts or stakeholders. This can minimize the risk of acting on the data, and increase the confidence and trust in the data analysis. 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
*Business Data Analytics (IIBA®-CBDA Exam preparation) | Udemy, Section 4: Interpret and Report Results, Lecture 20: Data Validation and Verification
NEW QUESTION # 45
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. Heteroskedacity
- B. Normality
- C. Variation
- D. Linearity
Answer: C
Explanation:
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 # 46
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. By ranking, it provided additional insight on how the attendee performed in comparison to other attendees
- B. The percentile score provides value by assessing the attendee's score against the average score for that exam
- C. 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
- D. The percentile score does not add any additional value in assessing the attendee's performance
Answer: A
Explanation:
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 # 47
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 quality
- B. Data architecture
- C. Data ethics
- D. Data governance
Answer: D
Explanation:
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 # 48
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. 80,80
- B. 79.84, 81.40
- C. 80, 83.14
- D. 83.14, 80
Answer: D
Explanation:
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 # 49
An analyst is using a Data Flow Diagram (DFD) to depict the flow of data across a data security company.
Which of the following is true about DFDs?
- A. Can illustrate a sequence of activities
- B. Are used to model data attributes
- C. Can be categorized as Logical or Physical
- D. Provide similar information as process flows
Answer: C
Explanation:
Explanation
A Data Flow Diagram (DFD) is a technique that shows the flow of data among processes, data stores, and external entities in a system. DFDs can be categorized as logical or physical, depending on the level of detail and abstraction. A logical DFD focuses on the business functions and data flows, without specifying the implementation details. A physical DFD shows the actual components and mechanisms that are involved in the data flow, such as hardware, software, files, and network connections. References:
*10.13 Data Flow Diagrams | IIBA® - International Institute of Business ..., menu, 10.13 Data Flow Diagrams
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 2: Source Data
*Introduction to Business Data Analytics: Organizational View, page 16, Figure 6: Data Flow Diagram
NEW QUESTION # 50
A consumer goods manufacturer has recently completed an analytics study to understand how to improve its operational excellence. From the top highlights, online sales outperformed other channels in sales growth and there was a direct relationship between positive customer reviews and increased internet sales. Which strategic business decision may be logically derived from these results?
- A. Improve quality of the products
- B. Improve operational efficiencies
- C. Create an empowered and collaborative work culture
- D. Encourage customers to complete online reviews
Answer: D
Explanation:
Explanation
The strategic business decision that may be logically derived from the results is to encourage customers to complete online reviews, because the results show that there is a direct relationship between positive customer reviews and increased internet sales. By increasing the number and quality of online reviews, the consumer goods manufacturer can boost its online sales performance, which outperformed other channels in sales growth. Online reviews can also help the manufacturer gain customer feedback, improve customer loyalty, and enhance its brand reputation. References:
*Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain 5: Use Results to Influence Business Decision Making
*Understanding the Guide to Business Data Analytics, page 9
*CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA®, page 8, CBDA Exam Sample Questions and Self-Assessment, Question 6
NEW QUESTION # 51
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