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| Section | Weight | Objectives |
|---|---|---|
| Visualization | 20% | - Visualization best practices - Chart and dashboard design principles - Data storytelling and reporting tools |
| Data Analysis | 25% | - Trend and pattern identification - Statistical methods and analysis techniques - Data interpretation and reporting |
| Data Mining | 25% | - Data manipulation and cleaning techniques - Data processing and transformation - Data collection and extraction methods |
| Data Concepts and Environments | 15% | - Data types, structures, and file formats - Data storage systems and platforms - Data lifecycle and data ecosystems |
| Data Governance, Quality, and Controls | 15% | - Compliance, privacy, and security controls - Data quality management - Data governance frameworks and policies |
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NEW QUESTION # 137
Which of the following best enables the retrieval and manipulation of data that is stored in a relational database?
Answer: C
Explanation:
This question pertains to theData Concepts and Environmentsdomain, focusing on tools for interacting with relational databases. The task is to identify the best method for retrieving and manipulating data.
* XML (Option A): XML is a data format, not a language for retrieving or manipulating database data.
* SQL (Option B): SQL (Structured Query Language) is specifically designed for querying and manipulating data in relational databases (e.g., SELECT, UPDATE), making it the best choice.
* Excel (Option C): Excel can analyze data but isn't designed for direct database manipulation.
* JavaScript (Option D): JavaScript is a programming language for web development, not optimized for relational database operations.
The DA0-002 Data Concepts and Environments domain includes understanding "different types of databases," and SQL is the standard language for relational database operations.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.
NEW QUESTION # 138
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?
Answer: A
NEW QUESTION # 139
A data analyst is creating a report about cars sold within the last twelve months. The current data set only contains information from the last ten months. Which of the following is the most appropriate way to accomplish this task?
Answer: C
NEW QUESTION # 140
Which of the following should a data analyst use to most efficiently gather recently released statistical information from one site?
Answer: D
Explanation:
An application programming interface (API) provides an efficient, automated way to retrieve the latest statistical data directly from a site in a structured format.
NEW QUESTION # 141
A data analyst receives a request for the current employee head count and runs the following SQL statement:
SELECT COUNT(EMPLOYEE_ID) FROM JOBS
The returned head count is higher than expected because employees can have multiple jobs. Which of the following should return an accurate employee head count?
Answer: B
Explanation:
This question falls under theData Analysisdomain of CompTIA Data+ DA0-002, which involves using SQL queries to analyze data and address issues like duplicates in datasets. The issue here is that the initial query counts all instances of EMPLOYEE_ID in the JOBS table, but employees can have multiple jobs, leading to an inflated head count. The goal is to count unique employees.
* SELECT JOB_TYPE, COUNT DISTINCT(EMPLOYEE_ID) FROM JOBS (Option A): This query is syntactically incorrect because COUNT DISTINCT(EMPLOYEE_ID) should use parentheses as COUNT(DISTINCT EMPLOYEE_ID). It also groups by JOB_TYPE, which is unnecessary for a total head count.
* SELECT DISTINCT COUNT(EMPLOYEE_ID) FROM JOBS (Option B): This query is incorrect because DISTINCT applies to the rows returned, not the COUNT function directly. It doesn't address the duplicate EMPLOYEE_ID issue.
* SELECT JOB_TYPE, COUNT(DISTINCT EMPLOYEE_ID) FROM JOBS (Option C): While this query correctly uses COUNT(DISTINCT EMPLOYEE_ID) to count unique employees, grouping by JOB_TYPE breaks the count into separate groups, which isn't required for a total head count.
* SELECT COUNT(DISTINCT EMPLOYEE_ID) FROM JOBS (Option D): This query correctly counts only unique EMPLOYEE_IDs by using the DISTINCT keyword within the COUNT function, providing an accurate total head count without grouping.
The DA0-002 Data Analysis domain emphasizes "given a scenario, applying the appropriate descriptive statistical methods using SQL queries," which includes handling duplicates with functions like COUNT (DISTINCT). Option D is the most direct and accurate method for a total unique head count.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
NEW QUESTION # 142
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