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, p

, 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. Reference: 1: Guide to Business Data Analytics, IIBA, 2020, p. 22.

According to the Guide to Business Data Analytics, PERT (Program Evaluation and Review Technique)

is a type of estimation that uses three values: optimistic, pessimistic, and most likely. The PERT

estimate is calculated as the weighted average of these three values, with more weight given to the

most likely value. PERT can be used to estimate the duration, cost, or other variables of a project or

activity, taking into account the uncertainty and variability of the dat

a. PERT can help provide a realistic and reliable estimate based on the available information.

Reference: Guide to Business Data Analytics, page 54-55; CBDA Exam Blueprint, page 7; [Introduction

to Business Data Analytics: A Practitioner View], page 16.

A qualitative open-ended question is a question that allows the respondent to express their

thoughts, feelings, or opinions in their own words, without being constrained by predefined options

or categories. A qualitative open-ended question can help the interviewer explore the underlying

reasons, motivations, or perceptions of the respondent. Option A is a qualitative open-ended

question, because it asks the respondent to explain how call volume affects their job satisfaction and

well-being, which may vary from person to person and require elaboration. Options B, C, and D are

not qualitative open-ended questions, because they ask the respondent to choose between two

alternatives (B and D) or provide a numerical value ©, which are quantitative and closed-ended

responses. Reference:

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Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain

2: Source Data

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Understanding the Guide to Business Data Analytics, page 14

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CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA®, page 8, CBDA Exam

Sample Questions and Self-Assessment,

The question “How effective is our marketing spend?” is too broadly scoped to be effectively

answered, because it is a vague and ambiguous question that does not specify the criteria, scope, or

timeframe for measuring the effectiveness of the marketing spend. The question also does not

define what constitutes marketing spend, or how it relates to the sales data or the budget

allocations. The question needs to be refined and clarified to make it more focused, relevant, and

feasible for the analytics team to answer. For example, the question could be rephrased as “How

does the marketing spend per channel affect the sales revenue and customer retention rate in the

last quarter?” Reference:

•

Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain

1: Identify the Research Questions

•

Understanding the Guide to Business Data Analytics, page 10-11

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CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA®, page 8, CBDA Exam

Sample Questions and Self-Assessment,

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. Reference:

Certification in Business Data Analytics (IIBA ® - CBDA), IIBA, accessed on January 20, 2024.

Business Data Analytics Certification - CBDA Competencies | IIBA®, IIBA, accessed on January 20,

2024.

Guide to Business Data Analytics, IIBA, 2020, p. 17-18.

What is Streaming Analytics? | Google Cloud, Google Cloud, accessed on January 20, 2024.

What is Data Integration? | IBM, IBM, accessed on January 20, 2024.

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. Reference: 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.

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

According to the Introduction to Business Data Analytics: A Practitioner View, churn rate is a measure

of customer attrition, or the percentage of customers who stop using a product or service over a

given time period. Churn rate is an important indicator of customer satisfaction, loyalty, and

retention. A high churn rate implies that customers are dissatisfied or have found better alternatives,

which can negatively affect the revenue and growth of a business. A low churn rate implies that

customers are satisfied and loyal, which can positively affect the revenue and growth of a business.

In this situation, the telecommunications company wants to increase their efforts on retaining

customers, so they need to track their churn rate and try to reduce it.

Reference: Introduction to Business Data Analytics: A Practitioner View, page 17; CBDA Exam

Blueprint, page 7; [Churn Rate Definition - Investopedia]

According to the Business Data Analytics: A Decision-Making Paradigm1, one of the key steps in the

analytics process is to communicate insights and recommendations to stakeholders. The analyst

should present the findings in a clear and concise manner, and provide actionable suggestions to

improve the business outcomes. In this case, the analyst has identified that repeat visitors are not

completing a sale, which indicates a possible issue with the sales checkout process. Therefore, the

analyst should recommend the retailer to streamline the sales checkout process, which could reduce

friction, increase customer satisfaction, and boost sales conversion rates for repeat visitors.

Reference: Business Data Analytics: A Decision-Making Paradigm

The average time for conversion is the average number of days it takes to convert a lead into a

customer. This is an important question to consider when evaluating sales performance, because it

indicates the efficiency and effectiveness of the sales process. A shorter time for conversion means

that the sales team can close more deals in less time, and thus increase the revenue and profitability

of the company. A longer time for conversion may indicate that there are bottlenecks, challenges, or

inefficiencies in the sales process that need to be addressed. Reference:

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Business Analysis Certification in Data Analytics, CBDA | IIBA®, CBDA Competencies, Domain

5: Use Results to Influence Business Decision Making

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Understanding the Guide to Business Data Analytics, page 9

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Business Data Analytics (IIBA®-CBDA Exam preparation) | Udemy, Section 4: Interpret and

Report Results, Lecture 19: Sales Performance Metrics