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CompTIA Data+ Certification Exam Sample Questions (Q235-Q240):

NEW QUESTION # 235
A database consists of one fact table that is composed of multiple dimensions. Depending on the dimension, each one can be represented by a denormalized table or multiple normalized tables. This structure is an example of a:

Answer: C

Explanation:
star schema is a type of database schema that consists of one fact table that is composed of multiple dimensions. A fact table contains quantitative measures or facts that are related to a specific event or transaction. A dimension table contains descriptive attributes or dimensions that provide context for the facts.
A star schema is called so because it resembles a star, with the fact table at the center and the dimension tables radiating from it. A star schema is a type of dimensional schema, which is designed for data warehousing and analytical purposes. Other types of dimensional schemas include snowflake schema and galaxy schema. A snowflake schema is similar to a star schema, except that some or all of the dimension tables are normalized into multiple tables. A galaxy schema consists of multiple fact tables that share some common dimension tables. A transactional schema is a type of database schema that is designed for operational purposes, such as recording day-to-day transactions and activities. A transactional schema is usually normalized to reduce data redundancy and improve data integrity. A non-relational schema is a type of database schema that does not follow the relational model, which organizes data into tables with rows and columns. A non-relational schema can store data in various formats, such as documents, graphs, key-value pairs, etc.


NEW QUESTION # 236
A salesperson who is prospecting potential clients collected the following data:

Which of the following is an issue with this data?

Answer: C


NEW QUESTION # 237
A database administrator needs to ensure only approved users can access specific database tables to perform financial functions. Which of the following is the best access control method for the administrator to use?

Answer: C

Explanation:
Access control is a critical aspect of database security. The best method for controllingwho can access financial databased onjob rolesisRole-Based Access Control (RBAC).
* Option A (Role-based):Correct.RBAC assigns permissions based on a user's role within the organization (e.g., accountants can access financial data, but sales representatives cannot).
* Option B (Rule-based):Incorrect. Rule-Based Access Control (RuBAC) enforces policies based on rules, such as time restrictions, rather than user roles.
* Option C (Discretionary):Incorrect. Discretionary Access Control (DAC) allows individual users to grant permissions, which can lead to security risks in financial systems.
* Option D (Group-based):Incorrect. Group-Based Access Control (GBAC) assigns permissions based on user groups, but RBAC provides finer control for financial functions.
Reference:The CompTIA Data+ exam emphasizesRBAC as a secure and efficient method for managing access to sensitive database tables.


NEW QUESTION # 238
Which one the following is not considered an aggregate function?

Answer: C

Explanation:
Explanation
The option that is not considered an aggregate function is SELECT. An aggregate function is a function that performs a calculation on a set of values and returns a single value. Examples of aggregate functions are SUM, MIN, MAX, AVG, COUNT, etc. SELECT is not an aggregate function, but a SQL command that is used to select data from a table or a query. Reference: SQL Aggregate Functions - W3Schools


NEW QUESTION # 239
While reviewing survey data, a research analyst notices data is missing from all the responses to a single question. Which of the following methods would BEST address this issue?

Answer: B

Explanation:
Explanation
This is because missing data is a type of data quality issue that occurs when data is absent or incomplete in a data set, which can affect the accuracy and reliability of the analysis or process. Missing data can be caused by various factors, such as human error, system error, or non-response. Missing data can be addressed by using various methods, such as replacing missing data, which means filling in or imputing the missing values with some reasonable estimates, such as mean, median, mode, or regression. The other methods are not used to address missing data. Here is why:
Remove duplicate data is a type of method that eliminates or reduces duplicate data, which is a type of data quality issue that occurs when data is repeated or copied in a data set. Removing duplicate data does not address missing data, but rather affects the quantity and validity of the data.
Replace redundant data is a type of method that eliminates or reduces redundant data, which is a type of data quality issue that occurs when data is unnecessary or irrelevant for the analysis or purpose.
Replacing redundant data does not address missing data, but rather affects the efficiency and performance of the analysis or process.
Remove invalid data is a type of method that eliminates or reduces invalid data, which is a type of data quality issue that occurs when data is incorrect or inaccurate in a data set. Removing invalid data does not address missing data, but rather affects the validity and reliability of the analysis or process.


NEW QUESTION # 240
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