DA0-002 Data Concepts and Environments Practice Test 6 — 15 Questions

Question 1

A marketing team needs to store customer feedback from social media posts, including text, images, and emojis. Which data concept is most appropriate for this storage?

Accepted Answer

Unstructured data in a NoSQL document database. Customer feedback from social media includes text, images, and emojis, which lack a predefined schema and are best stored as unstructured data. NoSQL document databases (e.g., MongoDB) store such data in flexible JSON-like documents, allowing each record to have varying fields and data types without requiring a fixed schema.

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Structured data in a relational database

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Unstructured data in a relational database

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Semi-structured data in an XML database

Question 2

An organization wants to assign responsibility for data quality and metadata management. Which role is primarily accountable for defining data standards and ensuring data quality across a specific domain?

Accepted Answer

Data steward. The data steward is the role primarily accountable for defining data standards and ensuring data quality within a specific domain. This aligns with the DAMA-DMBOK framework, where the data steward acts as the business-side owner of data content, establishing rules for data entry, validation, and metadata management to maintain consistency and accuracy.

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Data analyst

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Data owner

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Data custodian

Question 3

A data analyst notices that customer addresses in the database contain invalid ZIP codes. Which data quality dimension is being violated?

Accepted Answer

Validity. A is correct because validity refers to the degree to which data conforms to its defined format, rules, or constraints. Invalid ZIP codes (e.g., a five-digit code containing letters or a non-existent postal code) directly violate the format and domain rules expected for that field, making this a validity issue.

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Timeliness

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Consistency

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Completeness

Question 4

A company is implementing a data lifecycle management policy. Which stage occurs immediately after data is created?

Accepted Answer

Storage. In the data lifecycle management (DLM) model, the stage immediately following data creation is storage. Once data is generated or ingested, it must be persisted to a storage medium (e.g., disk, SSD, cloud object store) before any other operations like analysis, archival, or deletion can occur. This ensures data durability and availability for subsequent lifecycle stages.

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Deletion

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Archival

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Analysis

Question 5

To consolidate data from multiple operational databases into a central repository for reporting, a company decides to transform data before loading it into the target system. Which data integration approach is being used?

Accepted Answer

ETL (Extract, Transform, Load). The scenario describes transforming data before loading it into the target system, which is the defining characteristic of ETL (Extract, Transform, Load). In ETL, data is extracted from source systems, transformed in a staging area (e.g., cleaning, aggregating, joining), and then loaded into the central repository. This approach is commonly used when the target system (e.g., a data warehouse) requires pre-processed, high-quality data for reporting.

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Data virtualization

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Change data capture

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ELT (Extract, Load, Transform)

Question 6

A business needs to store large volumes of raw data in its native format for future analytics. Which storage architecture is most appropriate?

Accepted Answer

Data lake. A data lake is designed to store large volumes of raw data in its native format (structured, semi-structured, or unstructured) without requiring a predefined schema. This makes it ideal for future analytics where the data schema may not yet be known, as it supports schema-on-read rather than schema-on-write.

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Relational database

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Operational data store

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Data warehouse

Question 7

A data modeler is designing a dimensional model for a sales analytics system. The fact table contains sales transactions, and the dimension tables include product, customer, and time. To reduce data redundancy, the modeler normalizes the dimension tables into multiple related tables. Which schema is being implemented?

Accepted Answer

Snowflake schema. The snowflake schema is a dimensional model where dimension tables are normalized into multiple related tables to reduce data redundancy. In this scenario, the product, customer, and time dimensions are split into sub-dimensions (e.g., product category, customer geography, time hierarchy), which is the defining characteristic of a snowflake schema. This contrasts with a star schema where dimensions remain denormalized.

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Vault schema

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Star schema

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Galaxy schema

Question 8

An organization has multiple systems that store customer information inconsistently. To create a single authoritative view of customer data, they implement a process that identifies and merges duplicate records. This is an example of which data management discipline?

Accepted Answer

Master Data Management (MDM). Master Data Management (MDM) is the discipline that creates a single authoritative view of customer data by identifying and merging duplicate records across systems. Option A is incorrect because Data governance focuses on policies and standards, not directly on merging records. Option B is incorrect because Data warehousing consolidates data for reporting and analysis, not for creating a golden record of master data. Option C is incorrect because Data quality ensures accuracy and consistency but is a component of MDM, not the specific discipline for managing master data.

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Data governance

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Data warehousing

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Data quality

Question 9

A data governance team is drafting a policy for handling personally identifiable information (PII). According to data governance best practices, which document should define the classification levels and handling procedures?

Accepted Answer

Data classification policy. The data classification policy is the authoritative document that defines classification levels (e.g., public, internal, confidential, restricted) and specifies handling procedures for each category, including PII. This aligns with data governance best practices, as it establishes the rules for labeling, storing, transmitting, and disposing of sensitive data. A data dictionary describes metadata and schema, not classification rules.

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Data dictionary

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Data quality report

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Data flow diagram

Question 10

Which TWO of the following are considered internal data sources within an organization?

Accepted Answer

Employee payroll data. Employee payroll data (B) is generated and stored internally by an organization's HR or finance systems, making it an internal data source. Sales transaction records (D) are also generated internally through the organization's sales processes. Both are proprietary and not accessible from outside, fitting the definition of internal data. In contrast, social media feeds (A), government census data (C), and third-party market research (E) originate externally and are therefore external data sources.

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Social media feeds

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Government census data

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Market research reports from third parties

Question 11

Which THREE of the following are common characteristics of unstructured data?

Accepted Answer

Often stored in NoSQL databases or data lakes. Options B, C, and E are correct. Unstructured data lacks a predefined schema, can include various media types, and is often stored in NoSQL or data lakes. A is wrong because unstructured data is not stored in relational tables. D is wrong because SQL queries are not designed for unstructured data.

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Easily queried using SQL

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Stored in relational tables

Question 12

Which TWO of the following are primary benefits of implementing a data governance program?

Accepted Answer

Improved data quality and consistency. A primary benefit of a data governance program is improved data quality and consistency. Data governance establishes policies, standards, and procedures for data management, ensuring that data is accurate, complete, and reliable across the organization. This directly enhances decision-making and operational efficiency by reducing errors and inconsistencies in data assets.

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Faster data processing speed

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Increased data volume

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Lower storage costs

Question 13

Refer to the exhibit. The data shown is an example of which data concept?

Accepted Answer

Structured data. The exhibit shows data organized into rows and columns with a fixed schema (e.g., 'Name', 'Age', 'City'), which is the defining characteristic of structured data. Structured data conforms to a predefined data model, typically stored in relational databases or spreadsheets, and can be easily queried using SQL. This tabular format with consistent data types per column is the classic example of structured data.

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Unstructured data

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Metadata

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Semi-structured data

Question 14

Refer to the exhibit. Which data concept does this exhibit best represent?

Accepted Answer

JSON schema. The exhibit shows a structured data format with key-value pairs, arrays, and nested objects enclosed in curly braces, which is the standard syntax for JSON (JavaScript Object Notation). A JSON schema defines the structure, data types, and validation rules for JSON data, making it the best fit for the exhibit. The presence of fields like "name", "age", and "address" with specific types (e.g., string, integer) confirms this is a schema definition, not a generic data representation.

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Entity relationship diagram

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Data quality rule

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Data dictionary

Question 15

Refer to the exhibit. Which conclusion can be drawn from this data quality report?

Accepted Answer

The Email_Address column has a high uniqueness rate but needs improvement in validity.. The data quality report shows that the Email_Address column has a high uniqueness rate (e.g., 100% unique values), indicating no duplicate entries, but a low validity score (e.g., many entries fail format checks like missing '@' or domain). This means the column is structurally unique but contains invalid data, so it needs improvement in validity.

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The column is fully consistent but has low completeness.

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The column has low validity and low uniqueness.

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The column requires immediate action to improve completeness.