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ICDL Data Analytics study materials
ICDL Data Analytics study resources

ICDL Data Analytics (ICDL) practice questions

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Question 1Data Analytics Fundamentals

Which term describes raw, unprocessed facts and figures that have not yet been organised or interpreted?

  1. Metadata
  2. Data Correct answer.
  3. Knowledge
  4. Information

Explanation

Data consists of raw facts and figures collected from a source. Information is data that has been processed into a meaningful form, while knowledge is the understanding derived from information. Metadata describes data rather than being the data itself.

Question 2Data Analytics Fundamentals

A company stores customer records in a table where each row is one customer and each column is an attribute. What is this structure called?

  1. A text file
  2. A pivot cache
  3. A relational table Correct answer.
  4. A spreadsheet chart

Explanation

A relational table organises data into rows (records) and columns (fields or attributes). Each row represents a single entity and each column a property of that entity. Charts, caches and text files are not defined by this row-and-column record structure.

Question 3Data Analytics Fundamentals

Which data type is most appropriate for storing a customer's date of birth in an analytics dataset?

  1. Date Correct answer.
  2. Text
  3. Currency
  4. Boolean

Explanation

A date type stores calendar dates so they can be sorted chronologically and used in date calculations such as age. Text would sort incorrectly and prevent reliable date arithmetic. Currency and boolean types represent money and true/false values respectively.

Question 4Data Analytics Fundamentals

What does the acronym CSV stand for when referring to a common data file format?

  1. Coded String Vector
  2. Calculated Summary View
  3. Column-Sorted Variables
  4. Comma-Separated Values Correct answer.

Explanation

CSV stands for Comma-Separated Values, a plain-text format where fields are separated by commas and records by line breaks. It is widely used for exchanging tabular data between systems. The other expansions are not real data formats.

Question 5Data Analytics Fundamentals

In a dataset of employee salaries, which measure of central tendency is most affected by a single extremely high outlier?

  1. Range
  2. Mean Correct answer.
  3. Mode
  4. Median

Explanation

The mean adds all values and divides by the count, so one very large value pulls it upward. The median depends on position and the mode on frequency, so both resist extreme values. Range is a measure of spread, not central tendency.

Question 6Data Analytics Fundamentals

Which chart type is best suited to showing how a single numeric value changes over consecutive months?

  1. Histogram
  2. Pie chart
  3. Scatter plot
  4. Line chart Correct answer.

Explanation

A line chart plots values against an ordered axis such as time, making trends and changes easy to see. Pie charts show parts of a whole, scatter plots show relationships between two variables, and histograms show the distribution of one variable.

Question 7Data Analytics Fundamentals

Which of the following best describes a primary source of data?

  1. Data collected directly by the analyst for the current purpose Correct answer.
  2. An article citing another researcher's dataset
  3. A published industry benchmark table
  4. A government report summarising census results

Explanation

Primary data is collected first-hand by the person or organisation for the specific purpose at hand. Secondary data is data gathered by someone else and reused. Reports, benchmarks and cited datasets are all secondary sources.

Question 8Data Analytics Fundamentals

What is the main purpose of cleaning a dataset before analysis?

  1. To reduce the file size for storage
  2. To improve the accuracy and consistency of results Correct answer.
  3. To make charts more colourful
  4. To encrypt sensitive records

Explanation

Data cleaning addresses errors, duplicates, missing values and inconsistent formats so that analysis reflects reality. Its aim is trustworthy results, not storage, appearance or security. Those are separate concerns handled by other processes.

Question 9Data Analytics Fundamentals

A sales table records a value of 9999 in an age column where all other values range from 18 to 65. What type of data quality issue does this most likely represent?

  1. A missing value
  2. A duplicate record
  3. A data type mismatch
  4. An outlier Correct answer.

Explanation

An outlier is a value that lies far outside the normal range of the rest of the data. The value 9999 is implausibly high for an age and stands apart from the 18 to 65 pattern. Duplicates, missing values and type mismatches describe different problems.

Question 10Data Analytics Fundamentals

An analyst wants to count how many orders fall into each region category. Which operation should be used?

  1. Grouping with aggregation Correct answer.
  2. Sorting
  3. Transposing
  4. Filtering

Explanation

Grouping records by region and applying a count aggregation produces a total per category. Sorting orders rows, filtering removes rows, and transposing swaps rows and columns; none of these summarises counts per category.

Question 11Data Analytics Fundamentals

A dataset has a column of monthly revenue in dollars. Which summary statistic best communicates the typical monthly revenue when the data are skewed?

  1. The median Correct answer.
  2. The count
  3. The maximum
  4. The mean

Explanation

The median is resistant to skew because it depends on the middle position rather than the magnitude of extreme values. The mean can be distorted by a long tail, while the maximum and count do not describe a typical value.

Question 12Data Analytics Fundamentals

What does a correlation coefficient of -0.85 between advertising spend and customer complaints indicate?

  1. Higher spend causes more complaints
  2. As spend increases, complaints tend to decrease strongly Correct answer.
  3. There is no relationship between the variables
  4. Complaints increase in exact proportion to spend

Explanation

A correlation near -1 indicates a strong negative linear relationship: as one variable rises, the other tends to fall. Correlation does not establish causation, and it does not specify an exact proportional relationship. A value near zero would indicate no linear relationship.

Question 13Data Analytics Fundamentals

Which measure describes the average squared deviation of values from their mean?

  1. Variance Correct answer.
  2. Median
  3. Standard deviation
  4. Interquartile range

Explanation

Variance is the mean of the squared deviations from the mean. Standard deviation is the square root of variance, the median is a positional measure, and the interquartile range spans the middle 50 percent of values.

Question 14Data Analytics Fundamentals

A table of orders and a table of customers can be combined using a shared customer ID. What is this operation called?

  1. Appending
  2. Aggregating
  3. Joining Correct answer.
  4. Deduplicating

Explanation

A join combines two tables by matching values in a shared key column such as customer ID. Appending stacks rows with the same structure, aggregating summarises values, and deduplicating removes repeated records.

Question 15Data Analytics Fundamentals

What is the key difference between a bar chart and a histogram?

  1. A histogram shows the distribution of a continuous variable in bins Correct answer.
  2. A histogram always uses percentages
  3. A bar chart cannot display categories
  4. A bar chart uses numeric axes only

Explanation

A histogram groups a continuous variable into bins to show its distribution, with adjacent bars. A bar chart compares discrete categories with separated bars. Neither is restricted to numeric-only axes, and histograms can show counts or percentages.

Question 16Data Analytics Fundamentals

An analyst filters a sales dataset to records where the region equals 'North' and the amount is greater than 500. Which logical condition does this represent?

  1. An AND condition Correct answer.
  2. An XOR condition
  3. An OR condition
  4. A NOT condition

Explanation

Both criteria must be satisfied simultaneously, which is the definition of a logical AND. An OR condition would keep records meeting either criterion, NOT would exclude matches, and XOR would keep records meeting exactly one criterion.

Question 17Data Analytics Fundamentals

A dataset contains a column with values such as '12', 'unknown', and '7' in a field intended to hold whole numbers. Which issue is present?

  1. Duplicate rows
  2. Missing column headers
  3. Inconsistent data types Correct answer.
  4. Incorrect sorting

Explanation

Mixing numeric strings with non-numeric text in one field creates a data type inconsistency that prevents reliable arithmetic. Duplicate rows and missing headers describe other problems, and sorting is an operation rather than the underlying issue.

Question 18Data Analytics Fundamentals

What does the interquartile range measure?

  1. The most frequently occurring value
  2. The spread of the middle 50 percent of values Correct answer.
  3. The average deviation from the mean
  4. The distance from the lowest to the highest value

Explanation

The interquartile range is the difference between the third quartile and the first quartile, covering the middle half of the data. The full spread is the range, the most frequent value is the mode, and average deviation relates to mean absolute deviation.

Question 19Data Analytics Fundamentals

A dashboard is intended for executives who need a quick overview of key metrics. Which design choice best supports this?

  1. Using many bright colours for each data point
  2. Placing the most important indicators prominently at the top Correct answer.
  3. Displaying every raw record in a long table
  4. Hiding axis labels to save space

Explanation

Executive dashboards prioritise at-a-glance understanding, so key performance indicators should be placed prominently. Dense raw tables, excessive colour and missing labels all increase cognitive load and obscure the message.

Question 20Data Analytics Fundamentals

A survey question offers five fixed responses from 'strongly disagree' to 'strongly agree'. What type of data does this produce?

  1. Interval data
  2. Ordinal data Correct answer.
  3. Nominal data
  4. Ratio data

Explanation

Ordinal data has a meaningful order between categories but no defined numeric distance between them, which fits a Likert-style scale. Nominal data has no order, interval data has equal distances without a true zero, and ratio data has a true zero.

Question 21Data Analytics Fundamentals

An analyst notices that a report shows total revenue of 1,000,000 while the sum of the detail rows is 850,000. Which step should be taken first?

  1. Investigate whether some rows were excluded or duplicated Correct answer.
  2. Change the detail rows to match the total
  3. Publish the total figure and ignore the detail
  4. Delete the report and rebuild it from scratch

Explanation

A discrepancy between a total and its components signals a data integrity problem, such as filtered or duplicated rows. The correct first step is to diagnose the cause before altering or publishing anything. Overwriting values or discarding the work would conceal the underlying issue.

Question 22Data Analytics Fundamentals

A dataset of website visits contains a small number of sessions lasting several hours among thousands lasting a few minutes. Which statement about the distribution is most accurate?

  1. The distribution is symmetric around the mean
  2. The mean session length is pulled above the median Correct answer.
  3. The median is greater than the mean
  4. The mode best represents the typical session

Explanation

A small number of very long sessions creates a right-skewed distribution. In right-skewed data the mean is dragged toward the tail and exceeds the median. Symmetry would imply mean and median are close, and the mode is not the standard measure of typical value for continuous durations.

Question 23Data Analytics Fundamentals

Two analysts compute the average order value. One divides total revenue by the number of orders; the other divides by the number of customers. Why do their results differ?

  1. They are measuring different units of analysis Correct answer.
  2. One of them made an arithmetic error
  3. Averages cannot be computed from totals
  4. The revenue figure must be wrong

Explanation

The two calculations use different denominators, so they answer different questions: revenue per order versus revenue per customer. Both can be correct yet incomparable because the unit of analysis differs. Arithmetic error, incorrect revenue or an inability to average totals are not implied.

Question 24Data Analytics Fundamentals

A correlation of 0.6 is found between hours of training and productivity. Which conclusion is most defensible?

  1. Training guarantees higher productivity for every employee
  2. Training explains roughly 36 percent of the variance in productivity Correct answer.
  3. No relationship exists because 0.6 is below 0.8
  4. Training accounts for exactly 60 percent of productivity

Explanation

Squaring the correlation gives the coefficient of determination, so 0.6 squared is 0.36, meaning about 36 percent of the variance is shared. Correlation does not guarantee outcomes for individuals and does not equal a percentage of the variable itself. A value of 0.6 indicates a moderate positive relationship.

Question 25Data Analytics Fundamentals

An analyst merges a customer table with an orders table using an inner join. What is the result?

  1. Only customers who have at least one matching order Correct answer.
  2. Only orders that have no matching customer
  3. All orders, including those without a customer
  4. All customers, with blanks where no orders exist

Explanation

An inner join returns only rows where the key matches in both tables, so customers without orders are excluded. Keeping all customers with blanks would require a left join, and unmatched orders would appear only in a right or full outer join.

Question 26Data Analytics Fundamentals

Which term describes numerical facts that have been collected but not yet organized or interpreted?

  1. Insight
  2. Data Correct answer.
  3. Knowledge
  4. Information

Explanation

Data are raw, unprocessed facts such as numbers, text, or observations. Once data are organized and given context they become information, and interpretation leads to knowledge and insight.

Question 27Data Analytics Fundamentals

Which of the following is an example of unstructured data?

  1. A collection of customer review text Correct answer.
  2. A list of product prices
  3. A table of employee names and salaries
  4. A spreadsheet of monthly sales figures

Explanation

Unstructured data lack a predefined model or organization, such as free-form text in customer reviews. Spreadsheets, tables, and lists with defined columns are structured data.

Question 28Data Analytics Fundamentals

Which data type is most appropriate for storing a customer's date of birth in a database?

  1. Date Correct answer.
  2. Integer
  3. String
  4. Boolean

Explanation

A date of birth is a calendar date, so a date data type stores it correctly and allows date arithmetic such as calculating age. Using a text or number type would lose date semantics.

Question 29Data Analytics Fundamentals

What does the term 'data governance' refer to?

  1. The process of visualizing data in dashboards
  2. The hardware used to store large datasets
  3. The statistical methods used to test hypotheses
  4. The set of policies and standards for managing data quality, security, and access Correct answer.

Explanation

Data governance defines the rules, roles, and responsibilities for how data are collected, stored, protected, and used. It ensures data are trustworthy, secure, and compliant with regulations.

Question 30Data Analytics Fundamentals

A dataset records the number of children per household as 0, 1, 2, 3, or 4. Which measure of central tendency is most appropriate?

  1. Median
  2. Mean
  3. Mode Correct answer.
  4. Range

Explanation

The number of children is a discrete count with a limited set of values, so the mode identifies the most common household size. The mean can produce a non-integer value that does not correspond to a real count.

Question 31Data Analytics Fundamentals

Which of the following best describes a relational database?

  1. A file that stores all data in a single flat table
  2. A system that stores only unstructured text documents
  3. A collection of tables linked by shared key fields Correct answer.
  4. A spreadsheet with multiple worksheets

Explanation

A relational database organizes data into tables that are connected through primary and foreign keys, enabling consistent storage and flexible querying. This structure reduces redundancy and supports joins across related entities.

Question 32Data Analytics Fundamentals

What is the primary purpose of a data dictionary?

  1. To speed up query execution on large tables
  2. To store the actual data values for analysis
  3. To document the meaning, format, and constraints of each data element Correct answer.
  4. To encrypt sensitive data at rest

Explanation

A data dictionary is metadata that describes each field, its type, allowed values, and business meaning. It helps analysts and developers interpret data consistently and maintain quality.

Question 33Data Analytics Fundamentals

Which of the following is a key characteristic of big data commonly referred to as 'volume'?

  1. The sheer size or scale of the data Correct answer.
  2. The accuracy and trustworthiness of the data
  3. The speed at which data are generated and processed
  4. The variety of data formats and sources

Explanation

Volume refers to the massive scale of data, often measured in terabytes or petabytes. Velocity, variety, and veracity describe speed, format diversity, and quality respectively.

Question 34Data Analytics Fundamentals

An analyst wants to identify which product categories generate the highest total revenue. Which operation should be applied to the sales data?

  1. Count the number of rows per product category
  2. Sort the rows by revenue in ascending order
  3. Group the data by product category and sum revenue Correct answer.
  4. Filter the data to only the highest revenue row

Explanation

Grouping by category and summing revenue aggregates the data so that each category's total is computed. This allows direct comparison of total revenue across categories.

Question 35Data Analytics Fundamentals

A dataset contains a 'country' column with values 'USA', 'U.S.A.', and 'United States'. What data quality issue does this represent?

  1. Missing values
  2. Outdated records
  3. Inconsistent formatting Correct answer.
  4. Incorrect data type

Explanation

The same country is recorded in different formats, which is an inconsistency problem. Standardizing the values is necessary before grouping or joining on that field.

Question 36Data Analytics Fundamentals

Which statement correctly distinguishes a population from a sample?

  1. A sample is the entire set of items of interest
  2. A population and a sample always contain the same number of items
  3. A population includes all items of interest, while a sample is a subset Correct answer.
  4. A population is a subset of a sample

Explanation

The population is the complete group being studied, and a sample is a smaller subset selected from it. Analysts use samples to make inferences about the population when measuring every item is impractical.

Question 37Data Analytics Fundamentals

A dataset of employee ages has a mean of 40 and a median of 52. What does this suggest about the distribution?

  1. The distribution is negatively skewed Correct answer.
  2. The distribution has no outliers
  3. The distribution is symmetric
  4. The distribution is positively skewed

Explanation

When the mean is less than the median, the distribution is pulled toward lower values, indicating negative skew. The few unusually low ages drag the mean below the median.

Question 38Data Analytics Fundamentals

Which visualization is most suitable for comparing the proportions of a budget allocated to five departments?

  1. Scatter plot
  2. Pie chart Correct answer.
  3. Histogram
  4. Line chart

Explanation

A pie chart displays parts of a whole as slices, making it effective for showing proportional shares of a total. It works best with a small number of categories that sum to 100%.

Question 39Data Analytics Fundamentals

What is the purpose of a primary key in a database table?

  1. To sort the records automatically
  2. To link the table to an external file
  3. To uniquely identify each record in the table Correct answer.
  4. To store the most important numeric value

Explanation

A primary key is a column or combination of columns whose values are unique for every row, ensuring each record can be identified unambiguously. It also prevents duplicate rows and supports relationships with other tables.

Question 40Data Analytics Fundamentals

An analyst wants to combine two tables by matching all rows from the left table with matching rows from the right table, keeping unmatched left rows. Which join should be used?

  1. Full outer join
  2. Left outer join Correct answer.
  3. Right outer join
  4. Inner join

Explanation

A left outer join returns all rows from the left table and the matched rows from the right table, filling with nulls where no match exists. This preserves the complete left dataset.

Question 41Data Analytics Fundamentals

Which statement best describes the difference between a data warehouse and a data lake?

  1. A data warehouse and a data lake are identical in structure and purpose
  2. A data warehouse stores raw unstructured data, while a data lake stores only structured data
  3. A data warehouse is used only for real-time streaming, while a data lake is used for batch processing
  4. A data warehouse stores processed structured data, while a data lake stores raw data in various formats Correct answer.

Explanation

A data warehouse typically holds cleaned, structured data optimized for querying and reporting. A data lake retains raw data in native formats, including unstructured and semi-structured data, for flexible later use.

Question 42Data Analytics Fundamentals

A company wants to ensure that only authorized employees can view personally identifiable information. Which control addresses this requirement?

  1. Data compression
  2. Data deduplication
  3. Data archiving
  4. Access control Correct answer.

Explanation

Access control restricts who can view or modify data based on roles and permissions, protecting sensitive information. It is a core component of data security and privacy compliance.

Question 43Data Analytics Fundamentals

Which of the following is an example of secondary data?

  1. Data from a government census published for public use Correct answer.
  2. Observations recorded by the analyst during a field visit
  3. Responses collected from a survey the analyst designed
  4. Measurements taken during a controlled laboratory experiment

Explanation

Secondary data were originally collected by someone else for another purpose and are reused by the analyst, such as census data. Primary data are collected firsthand by the analyst for the current purpose.

Question 44Data Analytics Fundamentals

An analyst wants to compare the distribution of salaries between two departments. Which visualization is most appropriate?

  1. A line chart of monthly totals
  2. A single pie chart
  3. A scatter plot of salary versus age
  4. Side-by-side box plots Correct answer.

Explanation

Side-by-side box plots display the median, quartiles, and outliers for each group, making it easy to compare distributions across departments. They summarize spread and central tendency simultaneously.

Question 45Data Analytics Fundamentals

What does the term 'data lineage' describe?

  1. The process of deleting outdated records
  2. The statistical distribution of data values
  3. The physical location of servers storing data
  4. The documented path of data from origin through transformations to its current use Correct answer.

Explanation

Data lineage tracks the origin, movement, and transformations of data across systems, supporting traceability and auditability. It helps analysts understand where data came from and how it was changed.

Question 46Data Analytics Fundamentals

A dataset of customer transactions records the time of each purchase. Which analysis is best supported by this time field?

  1. Calculating the average price of a product
  2. Determining the number of unique customers
  3. Detecting seasonal patterns in purchasing behavior Correct answer.
  4. Identifying the most profitable product

Explanation

Time-stamped records allow analysts to aggregate transactions by period and detect recurring patterns such as seasonal peaks. This is a core use of temporal data in analytics.

Question 47Data Analytics Fundamentals

An analyst discovers that a dataset contains 15% missing values in a key variable. Which approach is most appropriate before analysis?

  1. Ignore the missing values and proceed with the analysis
  2. Replace all missing values with zero without checking
  3. Investigate the pattern of missingness and choose an appropriate imputation or exclusion method Correct answer.
  4. Delete the entire dataset

Explanation

The pattern of missing data determines whether values are missing at random or systematically, which guides the choice between imputation and exclusion. Blindly replacing or ignoring missing values can bias results.

Question 48Data Analytics Fundamentals

A company stores customer data in a cloud service and must comply with a regulation requiring data to remain within national borders. Which concept does this requirement illustrate?

  1. Data redundancy
  2. Data normalization
  3. Data sovereignty Correct answer.
  4. Data partitioning

Explanation

Data sovereignty is the principle that data are subject to the laws and governance of the country in which they are stored or collected. It often requires data to remain within national boundaries.

Question 49Data Analytics Fundamentals

An analyst joins two tables on a customer ID, but the customer ID is stored as text in one table and as an integer in the other. What is the most likely consequence?

  1. The join will automatically convert the data types correctly
  2. The join may fail or return no matches due to type mismatch Correct answer.
  3. The join will return all rows from both tables
  4. The join will succeed but return duplicate rows

Explanation

Joins require compatible data types for the key columns; a text-to-integer comparison may not match even when the underlying values appear identical. The analyst must harmonize the data types before joining.

Question 50Data Analytics Fundamentals

A dashboard shows a KPI that increased by 10% this month, but the underlying data are refreshed only quarterly. What is the most significant risk in interpreting the KPI?

  1. The KPI is calculated using the wrong formula
  2. The dashboard uses too many colors
  3. The displayed change may not reflect current conditions because the data are stale Correct answer.
  4. The KPI is based on a sample that is too large

Explanation

If the data are refreshed quarterly, a monthly change cannot be current; the KPI may reflect an older period. Decision-makers could act on outdated information, which is a data timeliness issue.