IIBA CBDA IIBA - CBDA Exam Practice Test Instant Access

Question 1

The architecture team puts forth a solution architecture that integrates multiple data sources from within and outside the organization. The architecture provides the foundation to source a new analytics program. If one of the objectives of the analytics team was to provide 'one source of the truth', this objective would be referring to which of the following?

AIdentifying one key stakeholder, who can make final decisions about which sources to relate/merge

BEvaluating the completeness, validity, and reliability of the data from source systems

CEnsuring stakeholders always have clear insight into the final requirements at all times

DEnforcing master data management principles and practices

Answer : D

Providing 'one source of the truth' means ensuring that there is a single, consistent, and authoritative source of data that can be used for analytics and decision making across the organization. This objective can be achieved by enforcing master data management principles and practices, which involve defining, governing, and maintaining the quality and integrity of the core data entities that are shared by multiple systems and processes. Master data management helps to eliminate data silos, reduce data duplication and inconsistency, and improve data accuracy and reliability12 Reference: 1: What is Master Data Management (MDM)? - Informatica 2: Master Data Management - IIBA BABOK Guide v3

Question 2

The CustomerOrder entity will include information on all customer orders. Applying database normalization rules, which set of attributes will need to be normalized to avoid redundancies?

* Customerld

* CustomerPhone

* Orderld

* OrderDate

* ProductName

* ProductQuantity

* OrderTotal

ACustomerPhone
ProductName

BProductName
ProductQuantity

COrderld
ProductName

DCustomerld
OrderDate

Answer : B

Database normalization is the process of organizing the data in a database to reduce redundancy and improve integrity, consistency, and performance1.Database normalization rules are based on the concept of normal forms, which are levels of database design that meet certain criteria2.One of the most common normal forms is the third normal form (3NF), which states that a table should not have any transitive dependencies, meaning that a non-key attribute should not depend on another non-key attribute3. In the CustomerOrder entity, the set of attributes that will need to be normalized to avoid redundancies are ProductName and ProductQuantity, as they are non-key attributes that depend on another non-key attribute, Orderld. This means that the same product information may be repeated for different orders, which could lead to data inconsistency, duplication, or update anomalies. To normalize this set of attributes, a separate table should be created for the OrderDetails entity, which would have Orderld, ProductName, and ProductQuantity as its attributes, and Orderld and ProductName as its composite primary key.

The other sets of attributes do not need to be normalized to avoid redundancies, as they do not violate the 3NF. CustomerPhone and ProductName are non-key attributes that depend on the primary key, Customerld and Orderld respectively, which is allowed by the 3NF. Orderld and ProductName are part of the composite primary key of the OrderDetails entity, which is also allowed by the 3NF.Customerld and OrderDate are both primary keys of the Customer and Order entities respectively, which are also allowed by the 3NF.

Question 3

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?

APlanned interviews are less effective than unplanned

BInterviews must be structured to be effective

CGoals for the interview should be clearly articulated

DInterviews should only be conducted with one interviewee

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. Reference:Guide to Business Data Analytics, page 25;Certification in Business Data Analytics Handbook, page 9;How to Ace Your Next Business Analysis Job Interview

Question 4

The sales department is interested in using business analytics to better understand their customer's purchasing habits. During the process of sourcing data, the analyst discovers geographic differences in how sales data is being recorded. The analyst would like to influence how the organization strategically plans for business analytics. Which practice, would move the organization closer to meeting this objective?

AData governance

BData integration

CData management

DData warehousing
Explanation:
Data governance is the practice of establishing and enforcing policies, standards, roles, and responsibilities for the quality, security, and usage of data across an organization1. Data governance helps ensure that data is consistent, reliable, and trustworthy, and that it aligns with the organization's strategic goals and objectives.Data governance also facilitates collaboration and communication among different stakeholders, such as business analysts, data owners, data stewards, and data consumers2.By implementing data governance, the analyst can influence how the organization strategically plans for business analytics, as data governance can help address the issues of data quality, data integration, data access, data ethics, and data value3.
Data integration, data management, and data warehousing are related but distinct concepts from data governance.Data integration is the process of combining data from different sources into a unified view4.Data management is the process of collecting, storing, organizing, and maintaining data throughout its lifecycle5. Data warehousing is the process of creating and maintaining a centralized repository of data for analytical purposes.While these practices can support business analytics, they do not necessarily influence how the organization strategically plans for business analytics, as they are more focused on the technical aspects of data rather than the organizational aspects of data.

Answer : A

Question 5

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?

ADescriptive

BDiagnostic

CDescriptive and Diagnostic

DDescriptive and Predictive
Explanation:
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.

Answer : D

Question 6

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?

ABullet chart

BDual axis chart

CBar chart

DPie chart

Answer : D

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. Reference: 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.

Question 7

A large number of text messages are received by Twitter each year making Twitter one example of Big Data. What data characteristic represents this large number of text messages?

AVeracity

BVelocity

CValue

DVariety

Answer : B

Velocity is one of the four V's of Big Data, along with Volume, Variety, and Veracity. Velocity refers to the speed at which data is generated, collected, and processed. A large number of text messages received by Twitter each year is an example of high-velocity data, as it requires real-time or near-real-time processing and analysis to extract insights and value from it. High-velocity data poses challenges and opportunities for business data analytics, as it requires efficient and scalable data infrastructure, streaming analytics, and timely decision-making.

IIBA CBDA Certification in Business Data Analytics IIBA - CBDA Exam Practice Test