DA0-002 Data Concepts and Environments Practice Test 4 — 15 Questions

Question 1

A retail analyst needs to determine the most popular product category. The dataset includes columns: ProductID, Category, SalesDate, QuantitySold, UnitPrice. Which column contains qualitative data?

Accepted Answer

Category. Qualitative data (also called categorical data) represents non-numeric categories or labels. The 'Category' column contains text values such as 'Electronics' or 'Clothing', which are descriptive and cannot be used in arithmetic operations. This makes it the only qualitative column in the dataset.

Answer

SalesDate

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QuantitySold

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UnitPrice

Question 2

A data scientist is building a model to predict customer churn. The company's internal CRM system provides customer demographics and transaction history. They also purchase demographic data from a third-party vendor. How should the purchased data be classified?

Accepted Answer

Secondary data. Purchased demographic data from a third-party vendor is classified as secondary data because it was originally collected by another entity for a different purpose and is being reused by the data scientist for churn prediction. Secondary data contrasts with primary data, which is collected firsthand for the specific analysis at hand. This classification is independent of whether the data is structured or unstructured.

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Internal data

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Structured data

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Primary data

Question 3

A logistics company is analyzing truck delivery times. Which variable is discrete?

Accepted Answer

Number of stops. A discrete variable is one that takes on a countable number of distinct values, often integers. The number of stops a truck makes is a count (e.g., 0, 1, 2, 3) and cannot be a fraction, making it a classic discrete variable in data analysis.

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Time taken in hours

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Fuel consumption in liters

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Distance traveled

Question 4

A hospital wants to analyze patient readmission rates. The data contains daily patient visits. What is the level of granularity?

Accepted Answer

Visit. The level of granularity refers to the finest detail captured in the dataset. Since the data contains daily patient visits, each record represents a single visit event, not the patient or the day itself. Therefore, 'Visit' is the correct granularity because each row corresponds to one visit occurrence.

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Patient

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Day

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Hospital

Question 5

A data analyst finds that the "Age" column contains values like "N/A", "unknown", and negative numbers. Which data quality dimension is primarily affected?

Accepted Answer

Validity. Validity refers to the degree to which data conforms to defined business rules or constraints. Invalid entries (non-numeric, negative) violate the expected data type and range.

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Accuracy

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Consistency

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Completeness

Question 6

An e-commerce company stores customer support emails in a text database, product images in a blob store, and sales transactions in a SQL table. Which data store holds only structured data?

Accepted Answer

SQL table. Structured data conforms to a predefined schema with rows and columns, enforcing data types and relationships. A SQL table is the canonical example of a structured data store because it organizes data into tables with fixed schemas, supports ACID transactions, and enables relational queries via SQL. In contrast, blob stores and text databases store unstructured or semi-structured data without a rigid schema.

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Blob store

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Text database

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None

Question 7

A market researcher conducts a survey with questions like "What is your favorite brand?" and "How many units do you purchase per year?" Which data types correspond?

Accepted Answer

Qualitative & Quantitative. 'favorite brand' is a categorical label (qualitative data), while 'units purchased per year' is a numerical count (quantitative data). The question explicitly pairs these two distinct data types, matching the definition of qualitative (non-numeric categories) and quantitative (numeric measurements).

Answer

Quantitative & Qualitative

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Both quantitative

Answer

Both qualitative

Question 8

In a customer database, each row represents a customer with columns: CustomerID, Name, Address, Phone. What does the column "Name" represent?

Accepted Answer

Attribute. In the context of a relational database, a column represents an attribute of an entity. The 'Name' column stores a specific characteristic (the customer's name) for each row, making it an attribute. This aligns with the data modeling concept where attributes define the properties of an entity.

Answer

Instance

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Entity

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Record

Question 9

A data audit reveals that some numbers in the "Revenue" column were manually entered from PDF invoices. This introduces potential errors. Which data concept is being addressed?

Accepted Answer

Data quality. The scenario describes a data audit that identifies potential errors from manual data entry from PDF invoices. This directly relates to data quality, which assesses aspects like accuracy, completeness, and consistency. The audit is highlighting a quality concern (potential errors), not lineage tracking. Data lineage focuses on the origin and transformation of data, but the primary issue here is the risk of inaccuracies, making data quality the correct concept.

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Data lineage

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Data security

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Data governance

Question 10

Which TWO data types are considered quantitative? (Select two.)

Accepted Answer

Customer satisfaction rating (1-5). Temperature in Celsius is quantitative because it is a continuous numerical measurement on an interval scale, allowing for meaningful arithmetic operations. Customer satisfaction rating (1-5) is also quantitative because the numbers represent a measurable quantity (level of satisfaction) that can be averaged and compared, often treated as interval data in business analytics. The other options are categorical: Product color is nominal, Zip code and Employee ID are nominal identifiers.

Answer

Product color

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Zip code

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Employee ID

Question 11

Which THREE characteristics describe unstructured data? (Select three.)

Accepted Answer

Contains text, images, audio, video. Unstructured data lacks a predefined data model and is typically composed of non-tabular formats such as text, images, audio, and video. Unlike structured data, it cannot be directly stored in relational databases without transformation. This characteristic is fundamental to distinguishing unstructured data from structured or semi-structured types.

Answer

Easily processed by standard SQL

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Organised in rows and columns

Question 12

Which TWO are examples of primary data? (Select two.)

Accepted Answer

Customer survey responses collected by the company themselves. Primary data is collected directly by the researcher or organization for a specific purpose. Customer survey responses gathered by the company itself are firsthand, original data that have not been previously published or aggregated by an external source. This aligns with the definition of primary data as original, unprocessed information collected from the source.

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Industry reports from a trade association

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Government census data

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Social media data purchased from a vendor

Question 13

Refer to the exhibit. Which type of data is the field "region"?

Accepted Answer

Qualitative. The field 'region' contains categorical labels (e.g., 'North', 'South', 'East', 'West') that represent distinct groups or categories, not numerical measurements. Qualitative data (also called categorical data) describes attributes or characteristics that can be named but not meaningfully ordered or measured on a numeric scale. Since 'region' assigns a name to a geographic area without any inherent numeric value or order, it is a classic example of qualitative data.

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Continuous

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Quantitative

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Discrete

Question 14

Refer to the exhibit. Based on the data profiling results, what is a likely data quality issue?

Accepted Answer

Validity. The min of 0 and max of 150 are biologically implausible for age. A 0-year-old or 150-year-old customer likely indicates invalid data, affecting validity.

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Completeness

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Accuracy

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Consistency

Question 15

Refer to the exhibit. Which data quality dimension is compromised by the missing value for Charlie's salary?

Accepted Answer

Completeness. Completeness measures whether all required data is present. Charlie's missing salary value means the record is incomplete, directly violating this dimension. In data quality frameworks, completeness is assessed by the proportion of non-null values in a field, and a null salary here fails that check.

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Uniqueness

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Timeliness

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Accuracy