Google Data Analytics Certificate 2025 — 60 Q&A Complete
Study Guide
Series:
CrashCourses Professional Study Series
Author:
Dr Z. Moomba, MBChB, MRCPsych | BethelWellness Ltd
Exam Target:
Google Data Analytics
Year:
2025/2026
Format:
60 Questions with Verified Answers and Rationales
>
Author's Note:
This document is an original work produced for the CrashCourses Professional Study Series.
Clinical questions and professional scenarios were composed by Dr Z. Moomba based on current
exam objectives, published guidelines, and evidence-based sources (2024–2025). All patient
names, ages, and case details are fictional. Any resemblance to existing published Q&A banks is
coincidental. For personal study use only — not for reproduction or redistribution.
PART 1: CORE PRINCIPLES & FOUNDATIONS
1.
A senior data analyst at a London teaching hospital is asked to investigate why outpatient
cardiology wait times have surged over the past quarter. Following the standard Google data
analysis framework, what is the initial step they must take before querying any database logs?
A) Structure the raw datasets
B) Formulate the right questions
C) Clean the retrieved information
D) Synthesise the final findings
,Answer: B
Rationale:
Lead: The first stage of the data lifecycle is the "Ask" phase, which requires analysts to clearly
define the business problem, identify stakeholder needs, and establish the specific questions
the data must answer.
Discriminator: Without defining precise metrics (e.g., referral-to-treatment time vs. time-in-
waiting-room), subsequent data collection will lack focus and utility.
Distractor: Structuring the raw datasets (A) is a component of the "Prepare" phase, which
cannot occur until the core questions are finalized.
Examiner Insight: The six sequential phases of data analysis are Ask, Prepare, Process,
Analyse, Share, and Act. [Google Data Analytics 2025]
2.
During an information governance audit of a regional diabetes registry, an analyst discovers that
the "Diagnosis Date" field contains disparate formats such as "12-05-2023", "2023/05/12", and
text entries like "May 12, 2023". Which foundational data concept best defines this specific
problem?
A) Systemic reporting bias
B) Information privacy breach
C) Data formatting inconsistency
D) Unintentional record duplication
Answer: C
Rationale:
Lead: Data inconsistency arises when identical variables are logged using conflicting formats,
units, or structures, hindering computational analysis.
Discriminator: The presence of multiple date formats in a single column directly violates the
principle of uniform data structuring, requiring normalisation before chronological functions can
operate.
Distractor: Systemic reporting bias (A) involves skewed data collection that misrepresents a
population, rather than a technical formatting error.
High-Yield Point: Consistent data typing is an absolute prerequisite for accurate temporal
aggregations in SQL or Python. [DAMA-DMBOK 2024]
,3.
A clinical researcher is examining the distribution of recorded heights among 500 toddlers in a
longitudinal study. To understand the single height measurement that appears most frequently in
this cohort, which statistical metric must they calculate?
A) The arithmetic average
B) The middle threshold
C) The dispersion metric
D) The most recurrent value
Answer: D
Rationale:
Lead: The mode represents the data point that occurs with the highest frequency within a given
set of values.
Discriminator: Identifying the "most frequently" occurring measurement is the exact
mathematical definition of the mode.
Distractor: The arithmetic average (A) calculates the mean, which can be heavily skewed by
extreme outliers and may not represent a value that actually exists in the dataset.
Clinical Pearl: The mode is uniquely valuable in clinical datasets for analyzing discrete
categorical data, such as the most common blood type or presenting symptom. [StatPearls
2025]
4.
To meet strict regulatory standards, a healthcare data team organizes electronic prescribing
records into tables featuring strictly defined rows and columns. Each column captures a distinct
attribute, such as "Patient_NHS_Number", "Medication", and "Dosage". What classification of data
architecture does this represent?
A) Free-text data
B) Loosely organized data
C) Relational structured data
D) Subjective observational data
Answer: C
Rationale:
, Lead: Structured data conforms to a rigid, predefined data model, universally organized into
tabular formats containing distinct rows and columns.
Discriminator: The explicit structuring of defined attributes (NHS numbers, medications) into
grid-like tables is the hallmark of a structured relational database.
Distractor: Free-text data (A) refers to unstructured formats like raw clinical notes or audio
files, which lack a predictable tabular schema.
Key Principle: Structured data is highly optimized for rapid querying and aggregation using
Relational Database Management Systems (RDBMS). [AWS Docs 2025]
5.
While auditing digital triage forms from an urgent care centre, an analyst identifies 50 rows where
the mandatory "Pain Scale (1-10)" field is completely empty. In standard data preparation
terminology, what are these empty fields called?
A) Statistical anomalies
B) Null values
C) Redundant entries
D) Parsing errors
Answer: B
Rationale:
Lead: In database management, a null value explicitly denotes the absence of data or an
unknown variable in a specific record field.
Discriminator: A completely blank numerical entry in a dataset is processed by standard
analytical software not as a zero, but as a NULL.
Distractor: Statistical anomalies (A) or outliers represent actual values that deviate massively
from the norm (e.g., a pain score of 99), not a lack of data.
Examiner Insight: Analysts must purposefully decide how to handle nulls—either via imputation
or exclusion—before running predictive algorithms. [Data Quality Assessment 2024]
6.
A procurement officer is tasked with merging two extensive inventory spreadsheets: one listing
surgical equipment IDs with descriptions, and the second listing identical IDs with current stock
levels. Which formula is explicitly designed to cross-reference and pull the stock levels into the
main sheet using the equipment ID?
A) Conditional counting
B) Vertical lookup linking
Study Guide
Series:
CrashCourses Professional Study Series
Author:
Dr Z. Moomba, MBChB, MRCPsych | BethelWellness Ltd
Exam Target:
Google Data Analytics
Year:
2025/2026
Format:
60 Questions with Verified Answers and Rationales
>
Author's Note:
This document is an original work produced for the CrashCourses Professional Study Series.
Clinical questions and professional scenarios were composed by Dr Z. Moomba based on current
exam objectives, published guidelines, and evidence-based sources (2024–2025). All patient
names, ages, and case details are fictional. Any resemblance to existing published Q&A banks is
coincidental. For personal study use only — not for reproduction or redistribution.
PART 1: CORE PRINCIPLES & FOUNDATIONS
1.
A senior data analyst at a London teaching hospital is asked to investigate why outpatient
cardiology wait times have surged over the past quarter. Following the standard Google data
analysis framework, what is the initial step they must take before querying any database logs?
A) Structure the raw datasets
B) Formulate the right questions
C) Clean the retrieved information
D) Synthesise the final findings
,Answer: B
Rationale:
Lead: The first stage of the data lifecycle is the "Ask" phase, which requires analysts to clearly
define the business problem, identify stakeholder needs, and establish the specific questions
the data must answer.
Discriminator: Without defining precise metrics (e.g., referral-to-treatment time vs. time-in-
waiting-room), subsequent data collection will lack focus and utility.
Distractor: Structuring the raw datasets (A) is a component of the "Prepare" phase, which
cannot occur until the core questions are finalized.
Examiner Insight: The six sequential phases of data analysis are Ask, Prepare, Process,
Analyse, Share, and Act. [Google Data Analytics 2025]
2.
During an information governance audit of a regional diabetes registry, an analyst discovers that
the "Diagnosis Date" field contains disparate formats such as "12-05-2023", "2023/05/12", and
text entries like "May 12, 2023". Which foundational data concept best defines this specific
problem?
A) Systemic reporting bias
B) Information privacy breach
C) Data formatting inconsistency
D) Unintentional record duplication
Answer: C
Rationale:
Lead: Data inconsistency arises when identical variables are logged using conflicting formats,
units, or structures, hindering computational analysis.
Discriminator: The presence of multiple date formats in a single column directly violates the
principle of uniform data structuring, requiring normalisation before chronological functions can
operate.
Distractor: Systemic reporting bias (A) involves skewed data collection that misrepresents a
population, rather than a technical formatting error.
High-Yield Point: Consistent data typing is an absolute prerequisite for accurate temporal
aggregations in SQL or Python. [DAMA-DMBOK 2024]
,3.
A clinical researcher is examining the distribution of recorded heights among 500 toddlers in a
longitudinal study. To understand the single height measurement that appears most frequently in
this cohort, which statistical metric must they calculate?
A) The arithmetic average
B) The middle threshold
C) The dispersion metric
D) The most recurrent value
Answer: D
Rationale:
Lead: The mode represents the data point that occurs with the highest frequency within a given
set of values.
Discriminator: Identifying the "most frequently" occurring measurement is the exact
mathematical definition of the mode.
Distractor: The arithmetic average (A) calculates the mean, which can be heavily skewed by
extreme outliers and may not represent a value that actually exists in the dataset.
Clinical Pearl: The mode is uniquely valuable in clinical datasets for analyzing discrete
categorical data, such as the most common blood type or presenting symptom. [StatPearls
2025]
4.
To meet strict regulatory standards, a healthcare data team organizes electronic prescribing
records into tables featuring strictly defined rows and columns. Each column captures a distinct
attribute, such as "Patient_NHS_Number", "Medication", and "Dosage". What classification of data
architecture does this represent?
A) Free-text data
B) Loosely organized data
C) Relational structured data
D) Subjective observational data
Answer: C
Rationale:
, Lead: Structured data conforms to a rigid, predefined data model, universally organized into
tabular formats containing distinct rows and columns.
Discriminator: The explicit structuring of defined attributes (NHS numbers, medications) into
grid-like tables is the hallmark of a structured relational database.
Distractor: Free-text data (A) refers to unstructured formats like raw clinical notes or audio
files, which lack a predictable tabular schema.
Key Principle: Structured data is highly optimized for rapid querying and aggregation using
Relational Database Management Systems (RDBMS). [AWS Docs 2025]
5.
While auditing digital triage forms from an urgent care centre, an analyst identifies 50 rows where
the mandatory "Pain Scale (1-10)" field is completely empty. In standard data preparation
terminology, what are these empty fields called?
A) Statistical anomalies
B) Null values
C) Redundant entries
D) Parsing errors
Answer: B
Rationale:
Lead: In database management, a null value explicitly denotes the absence of data or an
unknown variable in a specific record field.
Discriminator: A completely blank numerical entry in a dataset is processed by standard
analytical software not as a zero, but as a NULL.
Distractor: Statistical anomalies (A) or outliers represent actual values that deviate massively
from the norm (e.g., a pain score of 99), not a lack of data.
Examiner Insight: Analysts must purposefully decide how to handle nulls—either via imputation
or exclusion—before running predictive algorithms. [Data Quality Assessment 2024]
6.
A procurement officer is tasked with merging two extensive inventory spreadsheets: one listing
surgical equipment IDs with descriptions, and the second listing identical IDs with current stock
levels. Which formula is explicitly designed to cross-reference and pull the stock levels into the
main sheet using the equipment ID?
A) Conditional counting
B) Vertical lookup linking
