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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.
Data quality management
A.
Data quality management
Answers
B.
Database operations management
B.
Database operations management
Answers
C.
Data warehousing
C.
Data warehousing
Answers
D.
Meta data management
D.
Meta data management
Answers
Suggested answer: D

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.

Reference:

* 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

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.
Logistic regression
A.
Logistic regression
Answers
B.
Linkage algorithms
B.
Linkage algorithms
Answers
C.
Factor analysis
C.
Factor analysis
Answers
D.
K means clustering
D.
K means clustering
Answers
Suggested answer: C

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.

Reference:

* 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

An analyst is looking at a particular dataset that includes the scores across all 8th grade students, across three schools. The analyst is trying to determine which type of statistics average to use to best represent the results. On looking through the dataset, the analyst has identified a few extreme outliers. As a result, the analyst was led to use the following type of average:

A.
Median
A.
Median
Answers
B.
Range
B.
Range
Answers
C.
Mean
C.
Mean
Answers
D.
Mode
D.
Mode
Answers
Suggested answer: A

Explanation:

The median is the type of statistics average that the analyst should use to best represent the results, because it is a measure of central tendency that divides the data set into two equal halves. The median is the middle value of the data set when it is arranged in ascending or descending order. The median is not affected by extreme outliers, unlike the mean, which is the arithmetic average of the data set. The median can give a more accurate representation of the typical score of the 8th grade students across the three schools. Options B, C, and D are not types of statistics average, but types of statistics measures that describe other aspects of the data set. The range is a measure of dispersion that shows the difference between the highest and the lowest values of the data set. The mean is a measure of central tendency that shows the sum of the values of the data set divided by the number of values. The mode is a measure of central tendency that shows the most frequent value of the data set.

Reference:

* 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 13: Descriptive Statistics

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.
2017 minimum and maximum sales are higher than 2018, and the 2017 median result is higher than the 2018 median result
A.
2017 minimum and maximum sales are higher than 2018, and the 2017 median result is higher than the 2018 median result
Answers
B.
2017 minimum and maximum sales are higher than 2018, but the 2017 median result is lower than 2018 1st quartile result
B.
2017 minimum and maximum sales are higher than 2018, but the 2017 median result is lower than 2018 1st quartile result
Answers
C.
2018 minimum and maximum sales are higher than 2017, and the 2018 quartile results are higher than 2017 quartile results
C.
2018 minimum and maximum sales are higher than 2017, and the 2018 quartile results are higher than 2017 quartile results
Answers
D.
2018 minimum and maximum sales are higher than 2017, and the 2018 1st quartile is higher than 2017 median result
D.
2018 minimum and maximum sales are higher than 2017, and the 2018 1st quartile is higher than 2017 median result
Answers
Suggested answer: D

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
A.
information layer
Answers
B.
physical layer
B.
physical layer
Answers
C.
technical layer
C.
technical layer
Answers
D.
infrastructure layer
D.
infrastructure layer
Answers
Suggested answer: A

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

Reference: 1: Data and Analytics (D&A) - Gartner 2: Enterprise Data Analytics - SelectHub

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.
T-Testing
A.
T-Testing
Answers
B.
Simulation
B.
Simulation
Answers
C.
Visioning
C.
Visioning
Answers
D.
Storyboarding
D.
Storyboarding
Answers
Suggested answer: D

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

Reference: 1: Developing Key Messages for Effective Communication - MSKTC 2: 11 Ways Highly Successful Leaders Support Their Team - Redbooth

A database analyst is modelling a database for a large toy manufacturer. Which statement describes a logical database model?

A.
The layer of views created to summarize data or provide another perspective of certain data
A.
The layer of views created to summarize data or provide another perspective of certain data
Answers
B.
A model that depicts the actual design of the relational database
B.
A model that depicts the actual design of the relational database
Answers
C.
An abstraction of the conceptual data model that includes rules of normalization
C.
An abstraction of the conceptual data model that includes rules of normalization
Answers
D.
Modelling that involves objects being defined at the schema level
D.
Modelling that involves objects being defined at the schema level
Answers
Suggested answer: C

Explanation:

A logical database model is a data model of a specific problem domain expressed independently of a particular database management product or storage technology. It describes data using notation that corresponds to a data organization used by a database management system, such as relational tables and columns. It also includes rules of normalization, which are the process of converting complex data structures into simple, stable data structures12

Reference: 1: Logical schema - Wikipedia 2: What Is a Data Model? | Coursera

A professional association is funded by membership fees. The membership renewal occurs every 5 years. Although, they have a strong subscription rate each year, their renewal rate is low. They are working with an external firm specializing in Business Analytics to identify the groups of customers that have a high likelihood of cancelling their subscription after their first 5-year term ends. This type of study is called:

A.
Untrained learning
A.
Untrained learning
Answers
B.
Supervised learning
B.
Supervised learning
Answers
C.
Trained learning
C.
Trained learning
Answers
D.
Unsupervised learning
D.
Unsupervised learning
Answers
Suggested answer: D

Explanation:

Unsupervised learning is a type of study that involves finding patterns or clusters in data without any predefined labels or outcomes. It is useful for exploring data and discovering hidden structures or groups of customers. For example, the professional association can use unsupervised learning to identify the characteristics of customers who are likely to cancel their subscription after their first 5-year term ends, and then design strategies to retain them12

Reference: 1: What is Unsupervised Learning? - IBM 2: Unsupervised Learning - IIBA BABOK Guide v3

Which attributes from the Order entity will need to be normalized to avoid redundancies?

. Orderld

. OrderDate

. Itemld

. ItemName

. Quantity

. ItemPrice

A.
OrderDate ItemPrice
A.
OrderDate ItemPrice
Answers
B.
ItemName ItemPrice
B.
ItemName ItemPrice
Answers
C.
OrderDate ItemName
C.
OrderDate ItemName
Answers
D.
Item Name Quantity
D.
Item Name Quantity
Answers
Suggested answer: B

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

Reference: 1: Balancing Data Integrity and Performance: Normalization vs ... 2: Normalization Process in DBMS - GeeksforGeeks

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?

A.
Identifying one key stakeholder, who can make final decisions about which sources to relate/merge
A.
Identifying one key stakeholder, who can make final decisions about which sources to relate/merge
Answers
B.
Evaluating the completeness, validity, and reliability of the data from source systems
B.
Evaluating the completeness, validity, and reliability of the data from source systems
Answers
C.
Ensuring stakeholders always have clear insight into the final requirements at all times
C.
Ensuring stakeholders always have clear insight into the final requirements at all times
Answers
D.
Enforcing master data management principles and practices
D.
Enforcing master data management principles and practices
Answers
Suggested answer: D

Explanation:

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

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