Free Preparation Discussions
MENU
CompTIA DA0-001 Exam Questions
- Topic 1: Data Concepts and Environments: This topic covers fundamental concepts related to data schemas, dimensions, and data types, along with a comparison of common data structures and file formats.
- Topic 2: Data Mining: In this topic, you'll learn about data acquisition, the importance of data cleansing and profiling, techniques for data manipulation and query optimization to prepare data for analysis.
- Topic 3: Data Analysis: Here, the focus is on applying descriptive statistical methods to analyze data in scenarios, understanding inferential statistical methods, and exploring different types of analysis techniques along with tools commonly used in data analytics.
- Topic 4: Visualization: This topic explores translating business requirements into report formats, designing effective reports and dashboards using appropriate components, methods for dashboard development, and selecting suitable visualization types.
- Topic 5: Data Governance, Quality, and Controls: It covers essential concepts of data governance, applying data quality control techniques in scenarios, and understanding master data management (MDM) principles.
Free CompTIA DA0-001 Exam Actual Questions
Note: Premium Questions for DA0-001 were last updated On Jul. 11, 2025 (see below)
Which of the following defines the policies and procedures for managing the master data?
Comprehensive and Detailed In-Depth
Data governance encompasses the overall management of data availability, usability, integrity, and security within an organization. It involves establishing policies and procedures to ensure that data is managed effectively and consistently across the organization.
Option A:Data administration
Rationale:Data administration focuses on the technical aspects of managing data assets, including database management and maintenance. While important, it does not encompass the broader policy-making scope of data governance.
Option B:Data stewardship
Rationale:Data stewardship involves overseeing the lifecycle of data, ensuring its quality and proper usage. Stewards implement the policies set forth by data governance but do not define those policies themselves.
Option C:Data ownership
Rationale:Data ownership assigns responsibility for specific data assets to individuals or departments. Owners are accountable for the data but do not establish the overarching policies and procedures.
Option D:Data governance
Rationale:Data governance is the framework that defines the policies and procedures for managing master data, ensuring consistency, quality, and protection across the organization.
partners.comptia.org
Which of the following is an example of discrete data?
Comprehensive and Detailed In-Depth
Discrete data refers to countable, distinct values that cannot be subdivided meaningfully. These values are often whole numbers representing items that can be counted individually.
Option A:The number of employees at a company
Rationale:This represents discrete data because employees can be counted as individual units. You cannot have a fraction of an employee; thus, the data is countable and discrete.
Option B:The amount of rain that falls in a storm
Rationale:This represents continuous data, as rainfall can be measured in infinitely fine increments (e.g., millimeters, inches). The amount can take any value within a range.
Option C:The temperature at a weather station
Rationale:Temperature is continuous data because it can vary smoothly over a range and can be measured with fine precision (e.g., degrees Celsius or Fahrenheit).
Option D:The power consumption in a building
Rationale:Power consumption is continuous data, as it can be measured in units that allow for fractional values (e.g., kilowatt-hours) and can vary continuously over time.
partners.comptia.org
A healthcare data analyst notices that one data set in the column for BloodPressure contains several outliers that need to be replaced with meaningful values. Which of the following data manipulation techniques should the analyst use?
Comprehensive and Detailed In-Depth
In data analysis, handling outliers is crucial to ensure the accuracy and reliability of the dataset.Outliers can significantly skew statistical analyses and lead to misleading conclusions. One common method to address outliers isimputation, which involves replacing missing or anomalous data with substituted values based on other available information.
Option A:Recode
Rationale:Recoding involves changing the values of a variable to a different set of values, often to simplify categories or to correct data entry errors. While useful, recoding is not specifically aimed at addressing outliers.
Option B:Impute
Rationale:Imputation is the process of replacing missing or anomalous data points with substituted values, often derived from the dataset's statistical properties, such as the mean, median, or mode. This technique helps maintain the dataset's integrity by ensuring that analyses are not biased by missing or extreme values.
partners.comptia.org
Option C:Append
Rationale:Appending involves adding new data to the existing dataset, either by adding new rows (records) or columns (variables). This process does not address the issue of outliers within an existing column.
Option D:Reduction
Rationale:Reduction refers to decreasing the size or complexity of the dataset, such as by aggregating data or removing unnecessary variables. While it can help in simplifying data analysis, reduction does not specifically target the treatment of outliers.
Which of the following analysis techniques is an unsupervised data mining process?
Comprehensive and Detailed In-Depth
Unsupervised data mining techniques are used to identify hidden patterns or intrinsic structures in data without prior labels or classifications. Among the options provided,clusteringis a primary unsupervised learning method.
Option A:Clustering
Rationale:Clustering involves grouping a set of objects in such a way that objects in the same group (or cluster) are more similar to each other than to those in other groups. This technique is unsupervised because it doesn't rely on predefined labels and is used to discover natural groupings within data.
partners.comptia.org
Option B:Descriptive
Rationale:Descriptive analysis summarizes or describes the main features of a dataset, often through statistical measures or visualizations. While it provides insights into the data, it is not a data mining process but rather a preliminary step in data analysis.
Option C:Regression
Rationale:Regression analysis is a supervised learning technique used to model and analyze the relationships between variables. It requires labeled data to predict outcomes and is not considered an unsupervised process.
Option D:Predictive
Rationale:Predictive analysis involves using historical data to make predictions aboutfuture events. It often employs supervised learning techniques and relies on labeled datasets to train models.
An analyst wants to determine whether a relationship between an individual's age and voting preferences exists. Which of the following is the best statistical method for the analyst to use?
The Chi-squared test is used to analyze relationships between two categorical variables. In this case, age groups and voting preferences are both categorical variables, making chi-squared the most appropriate test.
- Select Question Types you want
- Set your Desired Pass Percentage
- Allocate Time (Hours : Minutes)
- Create Multiple Practice tests with Limited Questions
- Customer Support
Ettie
4 days agoGertude
19 days agoDexter
28 days agoWilliam
1 months agoLou
2 months agoKaran
3 months agoChandra
3 months agoMabel
4 months agoMona
4 months agoKarl
4 months agoMabelle
5 months agoFreeman
5 months agoAlline
5 months agoLavera
6 months agoCatarina
6 months agoFiliberto
6 months agoFannie
6 months agoRochell
6 months agoElvis
7 months agoNu
7 months agoVivan
7 months agoAnnamae
7 months agoHollis
7 months agoTanesha
8 months agoAvery
8 months agoDenny
8 months agoMadelyn
8 months agoHelene
8 months agoPaulina
9 months agoJamal
9 months agoJerry
9 months agoStefany
9 months agoKallie
9 months agoAlesia
10 months agoAmie
10 months agoFelicitas
10 months agoDelila
11 months agoAlbina
12 months agoAnnette
1 years agoAntione
1 years agoKrissy
1 years agoAlecia
1 years agoMarlon
1 years agoGarii
1 years agoalizabeth
1 years agokallis
1 years agojack
1 years agoShonda
1 years agoBette
1 years ago