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Exam DA0-002 Answers, DA0-002 New Braindumps Questions

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CompTIA Data+ Exam (2025) Sample Questions (Q35-Q40):

NEW QUESTION # 35
A table contains several rows of cellular numbers with call timestamps, call durations, called numbers, and carriers of the called number. Which of the following allows a data analyst to sort the cellular numbers based on the carriers of the called numbers and include the total call durations?

A. SELECT cellular_number, SUM(call_duration) FROM calls GROUP BY call_duration ORDERBY called_number_carrier;
B. SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY call_duration ORDER BY called_number_carrier;
C. SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number, called_number_carrier ORDER BY called_number_carrier;
D. SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number ORDER BY called_number_carrier;

Answer: C

Explanation:
This question falls under theData Analysisdomain of CompTIA Data+ DA0-002, focusing on SQL queries for data analysis. The task requires sorting cellular numbers by the carrier of the called number (called_number_carrier) and calculating the total call durations (SUM(call_duration)).
* Option A: SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number ORDER BY called_number_carrierThis query groups by cellular_number only, but called_number_carrier is in the SELECT clause without being in the GROUP BY, which is invalid in SQL (it would raise an error in most databases).
* Option B: SELECT cellular_number, SUM(call_duration) FROM calls GROUP BY call_duration ORDER BY called_number_carrierThis query doesn't include called_number_carrier in the SELECT clause, so it cannot be used in the ORDER BY clause, making it invalid. Grouping by call_duration also doesn't align with the task.
* Option C: SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY cellular_number, called_number_carrier ORDER BY called_number_carrierThis query correctly groups by both cellular_number and called_number_carrier (since both are in the SELECT clause), calculates the total call duration with SUM(call_duration), and sorts by called_number_carrier as required.
* Option D: SELECT cellular_number, called_number_carrier, SUM(call_duration) FROM calls GROUP BY call_duration ORDER BY called_number_carrierGrouping by call_duration is incorrect because cellular_number and called_number_carrier are in the SELECT clause but not in the GROUP BY, making this query invalid.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and Option C correctly aggregates and sorts the data as specified.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

NEW QUESTION # 36
A data engineer needs to create a reporting solution that has predefined filters and the ability to download .csv files. Which of the following is the best solution?

A. Generating a weekly executive summary
B. Creating a self-service portal on the company's intranet
C. Building an email template to request ad hoc reports
D. Developing a dynamic dashboard that refreshes daily

Answer: B

NEW QUESTION # 37
A data analyst is creating a forecast for a product line introduced early last year. Which of the following should the analyst use to create projected sales and customer satisfaction for next year?

A. Numerical and ordinal attributes
B. Standard deviation and constraints
C. Mean and median
D. Boolean data and an array

Answer: A

Explanation:
This question pertains to theData Analysisdomain, focusing on data types and methods for forecasting. The task involves projecting sales (numerical) and customer satisfaction (likely ordinal,e.g., ratings), requiring appropriate data attributes.
* Standard deviation and constraints (Option A): Standard deviation measures data spread, and constraints are conditions, neither of which directly supports forecasting.
* Mean and median (Option B): Mean and median are descriptive statistics, not sufficient for forecasting future values.
* Boolean data and an array (Option C): Boolean data (true/false) and arrays (data structures) are not relevant for forecasting sales and satisfaction.
* Numerical and ordinal attributes (Option D): Sales are numerical (e.g., units sold), and customer satisfaction is often ordinal (e.g., 1-5 ratings). These attributes are suitable for forecasting models (e.g., time-series analysis for sales, regression for satisfaction).
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and numerical and ordinal attributes are key for forecasting sales and satisfaction.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

NEW QUESTION # 38
A data analyst receives a new data source that contains employee IDs, job titles, dates of birth, addresses, years of service, and employees' birth months. Which of the following inconsistencies should the analyst identify?

A. Equivalence
B. Duplication
C. Redundancy
D. Parallel

Answer: C

Explanation:
This question falls under theData Governancedomain, focusing on identifying data quality issues. The dataset includes dates of birth and birth months, which suggests a potential inconsistency.
* Redundancy (Option A): The dataset includes both dates of birth (e.g., 1990-05-15) and birth months (e.g., May), which is redundant because the birth month can be derived from the date of birth, indicating a data quality issue.
* Equivalence (Option B): Equivalence isn't a standard data quality term in this context; it might refer to data matching, which isn't the issue here.
* Parallel (Option C): Parallel isn't a recognized data quality term; it might relate to processing, not data inconsistencies.
* Duplication (Option D): Duplication refers to identical records, but the issue here is redundant fields, not duplicate rows.
The DA0-002 Data Governance domain includes "data quality control concepts," and redundancy is a key inconsistency when the same information is stored in multiple forms unnecessarily.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 39
A data analyst is joining two tables with different content and one common field. Which of the following should the analyst do to most efficiently meet this requirement?

A. Create a cluster to facilitate data integration between the tables.
B. Explode both tables to identify unique values and reorder the fields in one table.
C. Match the records of the related columns and merge the tables.
D. Append the values of the matching columns and concatenate the other data fields.

Answer: C

Explanation:
This question falls under theData Acquisition and Preparationdomain, focusing on combining data from multiple tables. The tables have different content but share a common field, indicating a join operation.
* Match the records of the related columns and merge the tables (Option A): This describes a join operation, where records are matched on the common field (e.g., a key like Customer_ID) and the tables are merged, which is the most efficient method.
* Create a cluster to facilitate data integration between the tables (Option B): Clustering is a machine learning technique, not a method for joining tables.
* Explode both tables to identify unique values and reorder the fields in one table (Option C):
Exploding is used in nested data (e.g., JSON arrays), and this approach is overly complex and unnecessary.
* Append the values of the matching columns and concatenate the other data fields (Option D):
Appending stacks tables vertically, and concatenation applies to text, neither of which is appropriate for joining tables with a common field.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as joining tables using a common field.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.

NEW QUESTION # 40
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