IIBA-CBDA · IIBA · Updated August 2026
IIBA-CBDA practice questions
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1/10 · Source Data
A retail analytics team is cataloguing where the data for an upcoming customer-churn analysis will come from. Some data is generated and owned by the organization's own transactional systems, while other data must be obtained from third-party providers outside the organization. When classifying data sources, what best characterizes an EXTERNAL data source?
AData produced and maintained within the organization's own operational systems such as CRM and ERP
BAny data stored in a relational database regardless of who created or owns it
CData that has already passed data-quality validation and is ready for analysis
DData acquired from outside the organization, such as government datasets, social media, or purchased market data
Show answer & explanation
D is correct. The Source Data domain distinguishes internal sources (generated and owned by the organization, e.g., CRM, ERP, transactional systems) from external sources (acquired from outside, e.g., public/government data, social media, purchased datasets). The defining attribute of an external source is that the data originates beyond the organization's boundaries, independent of its storage technology or quality status.
↗ IIBA Business Data Analytics Guide — Source Data
2/10 · Analyze Data
A business data analyst is asked to summarize what has already happened with last quarter's sales by computing totals, averages, and the distribution of order values across regions. Which type of analytics best describes this work?
ADescriptive analytics
BPredictive analytics
CDiagnostic analytics
DPrescriptive analytics
Show answer & explanation
A is correct. The four common categories of analytics are descriptive (what happened), diagnostic (why it happened), predictive (what will happen), and prescriptive (what should be done). Computing totals, averages, and distributions of historical sales is a textbook example of descriptive analytics.
↗ IIBA Business Data Analytics Guide — Analyze Data
3/10 · Interpret and Report Results
A business data analyst has finished a regression model and produced summary statistics. Before sharing anything with stakeholders, what is the primary purpose of the activity that focuses on interpreting analytics results?
ATo translate the technical output of the analysis into meaningful, actionable understanding aligned to the original business questions
BTo re-run the model with additional features until the accuracy metric reaches a predetermined target
CTo clean and standardize the source data so the model can be executed without errors
DTo select the visualization software the organization will standardize on for all dashboards
Show answer & explanation
4/10 · Secure, Manage and Document Data
A business data analytics team is establishing accountability for how customer data is defined, accessed, and used across the organization. They want a framework that assigns decision rights and responsibilities, sets standards for data handling, and ensures policies are enforced consistently. Which discipline best describes what the team is putting in place?
AData wrangling
BData governance
CData visualization
DExploratory data analysis
Show answer & explanation
B is correct. Data governance provides the organizing framework of decision rights, accountability, standards, and policies that determine how data is defined, accessed, used, and protected. The other options are analytical or preparation activities that operate within—rather than establish—that framework.
↗ IIBA Business Data Analytics Guide — Secure, Manage and Document Data
5/10 · Identify the Research Questions
A regional grocery chain wants to reduce its perishable-food waste. The executive sponsor tells the analytics team, "Just go find something interesting in the inventory data." The lead business data analyst is concerned that this directive will produce analysis that no one can act on. To best frame the engagement, what should the analyst do first?
ASelect a predictive modeling algorithm appropriate for time-series inventory data and tune it for accuracy.
BDefine research questions that tie back to the specific business decision the sponsor needs to make about reducing perishable waste.
CBuild an executive dashboard of inventory KPIs so the sponsor can browse the data themselves.
DBegin profiling all available inventory tables to discover statistically significant correlations before defining any questions.
Show answer & explanation
B is correct. The first step in identifying research questions is to connect the analytics effort to a concrete business decision or problem. A directive to 'find something interesting' lacks decision context, so the analyst must reframe it into questions that, when answered, will inform a specific decision (here, how to reduce perishable waste). This ensures the analysis produces actionable insight rather than incidental findings.
↗ IIBA Business Data Analytics Guide — Identify the Research Questions
6/10 · Source Data
An analyst is inventorying inputs for a sentiment-analysis initiative. The inputs include customer support email bodies, scanned PDF complaint letters, and recorded call audio. None of these inputs conform to a predefined row-and-column schema. How should the analyst classify this category of data by structure?
AReference (master) data
BUnstructured data
CSemi-structured data
DStructured data
Show answer & explanation
B is correct. By structure, data is commonly classified as structured (fixed schema/tables), semi-structured (self-describing tags such as JSON/XML without a rigid schema), or unstructured (no predefined model — free text, images, audio, video). Support emails, scanned letters, and call audio have no predefined schema, making them unstructured.
↗ IIBA Business Data Analytics Guide — Source Data
7/10 · Analyze Data
Marketing leadership wants to understand which customer attributes are associated with higher churn so they can intervene before customers leave. The data analyst has a labeled historical dataset where each customer is flagged as churned or retained, and the goal is to assign new customers to one of these two groups. Which analytical technique is most appropriate?
ALinear regression
BClassification
CClustering
DAssociation rules
Show answer & explanation
B is correct. Choosing an analytical technique depends on the question and the data. When the outcome is a known, discrete category and labeled historical data is available, classification (a supervised technique) is the correct choice. Clustering applies to unlabeled data, regression to continuous outcomes, and association rules to co-occurrence patterns.
↗ IIBA Business Data Analytics Guide — Analyze Data
8/10 · Interpret and Report Results
An analyst observes that monthly ice-cream-adjacent product sales and the number of customer support tickets both rise and fall together across 18 months, yielding a correlation coefficient of 0.86. A manager wants to reduce support tickets by lowering product sales. What is the most appropriate guidance the analyst should give when interpreting this result?
ABecause both metrics move together, either one can be substituted for the other in future reporting to simplify dashboards
BThe strong association does not establish causation, and a lurking variable such as overall seasonal demand may drive both metrics
CReducing sales is justified because a coefficient of 0.86 demonstrates that sales drive support volume
DA correlation above 0.8 is always spurious, so the relationship should be discarded from the analysis entirely
Show answer & explanation
9/10 · Analyze Data · hard
An analyst plans to estimate customer satisfaction for an entire national customer base but can only survey a subset due to time and cost. To ensure the results can be generalized to the whole population, which sampling approach is most appropriate?
AInclude only the most loyal long-tenured customers, as they know the product best
BDraw a representative sample using a probability-based method so every customer has a known chance of selection
CSurvey only the customers who recently contacted support, because their responses are easiest to collect
DSurvey only customers in the single largest city, since that market has the most customers
Show answer & explanation
B is correct. When analyzing a subset of data to draw conclusions about a larger population, representativeness is critical. A probability-based sampling method, where each population member has a known chance of selection, minimizes bias and allows valid generalization. Convenience, geographic, or loyalty-based selections introduce systematic bias that distorts the estimate.
↗ IIBA Business Data Analytics Guide — Analyze Data
10/10 · Source Data · hard
A logistics company asks: 'Why have on-time delivery rates dropped in the Northeast region over the last two quarters?' An analyst must determine what source data is needed before any sourcing begins. Which approach BEST reflects sound practice for translating the business question into source data requirements?
AIdentify the metrics and dimensions the question implies — delivery timestamps, region, time period, and likely drivers — and let those requirements guide which sources to seek
BGather every available dataset in the data warehouse first, then decide afterward which question the data can answer
CDefault to whichever dataset has the highest data-quality score, regardless of its relevance to delivery performance
DChoose the dashboard layout and chart types that executives prefer, then source whatever data fits those visuals
Show answer & explanation
A is correct. Sound practice ties source-data requirements to a clearly framed business question: decompose the question into the metrics (on-time rate, delivery timestamps), dimensions (region, quarter), and plausible drivers, then seek sources that supply them. The distractors reverse the logic — collecting data first, letting visuals or convenience drive sourcing, or selecting data by quality score alone — all of which detach sourcing from the question being answered.
↗ IIBA Business Data Analytics Guide — Source Data
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IIBA-CBDA practice — FAQ
How many questions is the IIBA-CBDA exam and how long is it?
75 multiple-choice scenario-based questions in 120 minutes (2 hours).
What is the passing score for IIBA-CBDA?
IIBA does not publish a numeric cut score — results are pass/fail with per-area performance indicators. Aim for a consistent 80–85% on realistic mocks before booking.
What is the IIBA-CBDA pass rate?
IIBA does not publish official pass rates, so any exact percentage quoted online is unverified. The readiness signal that actually predicts passing: consistently holding 80–85% on realistic, full-length practice exams before you book.
What are the IIBA-CBDA eligibility requirements?
No mandatory requirements — open to anyone. IIBA recommends around 2 years of analysis work in business data analytics.
How much does IIBA-CBDA cost?
No application fee. Exam fee $250 for members ($405 non-members), first-year membership included.
How long should I study for IIBA-CBDA?
For most candidates, around 30–50 hours (no official IIBA figure). What matters most is practising questions and analysing why each option is right or wrong — not just reading.
Does the IIBA-CBDA certification need recertification?
20 Continuing Development Units (CDUs) every year.
Are ExamDeck's IIBA-CBDA questions exam dumps?
No — every question is original, written to test the concepts and reviewed before it ships, with an explanation linked to the source for every option. Dumps are stale, often wrong, and against IIBA's policies.
ExamDeck is an independent study tool, not affiliated with IIBA®. IIBA-CBDA and BABOK® are trademarks of the International Institute of Business Analysis. Exam facts checked against official IIBA materials (as of August 2026); confirm current details on iiba.org.