2025 DA0-001 Valid Exam Cram | Perfect 100% Free Latest DA0-001 Test Testking

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CompTIA Data+ Certification Exam Sample Questions (Q258-Q263):

NEW QUESTION # 258
Given the following customer and order tables:
Which of the following describes the number of rows and columns of data that would be present after performing an INNER JOIN of the tables?

A. Seven rows, eight columns
B. Five rows, eight columns
C. Nine rows, five columns
D. Eight rows, seven columns

Answer: A

Explanation:
This is because an INNER JOIN is a type of join that combines two tables based on a matching condition and returns only the rows that satisfy the condition. An INNER JOIN can be used to merge data from different tables that have a common column or a key, such as customer ID or order ID. To perform an INNER JOIN of the customer and order tables, we can use the following SQL statement:

This statement will select all the columns (*) from both tables and join them on the customer ID column, which is the common column between them. The result of this statement will be a new table that has seven rows and eight columns, as shown below:

The reason why there are seven rows and eight columns in the result table is because:
* There are seven rows because there are six customers and six orders in the original tables, but only five customers have matching orders based on the customer ID column. Therefore, only five rows will have data from both tables, while one row will have data only from the customer table (customer 5), and one row will have no data at all (null values).
* There are eight columns because there are four columns in each of the original tables, and all of them are selected and joined in the result table. Therefore, the result table will have four columns from the customer table (customer ID, first name, last name, and email) and four columns from the order table (order ID, order date, product, and quantity).

NEW QUESTION # 259
Which of the following are reasons to create and maintain a data dictionary? (Choose two.)

A. To specify user groups for databases
B. To improve data acquisition
C. To confine breaches of PHI data
D. To provide continuity through personnel turnover
E. To reduce processing power requirements
F. To remember specifics about data fields

Answer: D,F

Explanation:
A data dictionary is a collection of metadata that describes the data elements in a database or dataset. It can help improve data acquisition by providing information about the data sources, formats, quality, and usage. It can also help remember specifics about data fields, such as their names, definitions, types, sizes, and relationships. Therefore, options B and D are correct.
Option A is incorrect because it is not a reason to create and maintain a data dictionary, but a benefit of doing so.
Option C is incorrect because specifying user groups for databases is not a function of a data dictionary, but a function of a database management system or a security policy.
Option E is incorrect because confining breaches of PHI data is not a function of a data dictionary, but a function of a data protection or encryption system.
Option F is incorrect because reducing processing power requirements is not a function of a data dictionary, but a function of a data compression or optimization system.

NEW QUESTION # 260
Which of the following is an example of a data-mining ETL tool?

A. Stata
B. Cognos
C. SSIS
D. SPSS

Answer: C

Explanation:
A data-mining ETL tool is a software application that performs extract, transform, and load (ETL) operations on data for data mining purposes. Data mining is the process of discovering patterns, trends, and insights from large and complex data sets. ETL tools help to prepare the data for analysis by extracting data from various sources, transforming data into a consistent and suitable format, and loading data into a data warehouse or other destination. SSIS (SQL Server Integration Services) is an example of a data-mining ETL tool that is part of Microsoft SQL Server. SSIS provides graphical tools and wizards for building and debugging ETL packages that can work with various data sources and destinations. Therefore, the correct answer is A.
References: [Data Mining - SQL Server Integration Services (SSIS) | Microsoft Docs], [What Is Data Mining?
| Oracle]

NEW QUESTION # 261
Which of the following data types is best for representing count data?

A. Referential
B. Discrete
C. Sequential
D. Continuous

Answer: B

Explanation:
Comprehensive and Detailed In-Depth Explanation:
Count data refers to data that represents the number of occurrences of an event or the number of items in a set, which are whole numbers (integers). Understanding the nature of data types is crucial for accurate data analysis and representation.
* Discrete Data: This type of data consists of distinct, separate values. Discrete data is countable and often represents items that can be counted in whole numbers, such as the number of customers, defects, or occurrences. Since count data involves whole numbers, discrete data is the most appropriate representation.
* Referential Data: This pertains to data that establishes relationships between tables in a database, often using keys. It is not related to counting occurrences.
* Sequential Data: This involves data that follows a specific order or sequence, such as timestamps or ordered events. While it indicates order, it doesn't inherently represent count data.
* Continuous Data: This type of data can take any value within a range and is measurable rather than countable, such as height, weight, or temperature. Continuous data is not suitable for representing count data, as counts are discrete by nature.
Therefore, Discrete data is the best choice for representing count data, as it accurately reflects whole number counts of occurrences or items.

NEW QUESTION # 262
Given the diagram below:

Which of the following types of sampling is depicted in the image?

A. Random
B. Cluster
C. Systematic
D. Stratified

Answer: C

Explanation:
Explanation
Systematic sampling is a type of sampling where the sample is selected by following a fixed interval. For example, every 10th person in a list is chosen for the sample. In the image, the sample is selected by choosing every 3rd person in the line, starting from person number 1. This is an example of systematic sampling.
References: Types of Sampling Techniques in Data Analytics You Should Know, Sampling Methods | Types, Techniques & Examples - Scribbr

NEW QUESTION # 263
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2025 DA0-001 Valid Exam Cram | Perfect 100% Free Latest DA0-001 Test Testking

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CompTIA Data+ Certification Exam Sample Questions (Q258-Q263):

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