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| Section | Weight | Objectives |
|---|---|---|
| Data Concepts and Environments | 20% | - Data types, structures, and formats - Database systems and architectures - Foundational concepts of AI and machine learning in data - Cloud and distributed data environments |
| Data Analysis | 24% | - Analytical tools and querying languages - Statistical methods and techniques - Data modeling and pattern recognition - Exploratory and confirmatory data analysis |
| Data Governance, Quality, and Management | 14% | - Data governance frameworks and policies - Data lifecycle management and documentation - Data privacy, security, and compliance - Data quality standards and monitoring |
| Visualization and Reporting | 20% | - Communicating insights to stakeholders - Design principles for effective visualizations - Dashboard and report development - Validation and accuracy of reports |
| Data Acquisition and Preparation | 22% | - Data collection methods and sources - Data cleaning, validation, and quality improvement - Data extraction, transformation, and loading (ETL/ELT) - Data integration and normalization |
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NEW QUESTION # 100
A data analyst needs to combine the results of two separate queries that have similar data and the same number of columns. The output must also have distinct rows. Which of the following should the data analyst use?
Answer: C
Explanation:
A union combines the results of two separate queries into a single result set when the queries return the same number of columns with compatible data types. By default, UNION returns only distinct rows, removing duplicates from the combined output.
NEW QUESTION # 101
Which of the following is the most efficient to use when programming repeatable tasks?
Answer: D
Explanation:
This question pertains to theData Acquisition and Preparationdomain, focusing on tools for automating repeatable tasks in data processes. The task is to identify the most efficient programming method.
* LLM (Option A): Large Language Models (e.g., GPT) are for text generation, not efficient for repeatable data tasks.
* Deep learning (Option B): Deep learning is for complex pattern recognition (e.g., image classification), not efficient for simple repeatable tasks.
* NLP (Option C): Natural Language Processing is for text analysis, not general repeatable tasks.
* RPA (Option D): Robotic Process Automation (RPA) automates repetitive, rule-based tasks (e.g., data entry, file processing), making it the most efficient for programming repeatable tasks.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," and RPA is a widely used method for automating repeatable data tasks.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.
NEW QUESTION # 102
A company needs to display sales numbers on the intranet. This solution needs to be updated every day before the workday starts. Which of the following is the best solution to meet this objective?
Answer: A
Explanation:
A dynamic dashboard that refreshes nightly automatically updates the displayed sales data before employees begin work each day. This provides current information on the intranet without requiring manual report generation or distribution, making it the most efficient and reliable solution.
NEW QUESTION # 103
Which of the following data repositories stores unformatted data in its original, raw form?
Answer: A
Explanation:
This question pertains to theData Concepts and Environmentsdomain, focusing on data repositories. The task is to identify a repository that stores raw, unformatted data.
* Data warehouse (Option A): A data warehouse stores structured, processed data in a predefined schema, not raw data.
* Data silo (Option B): A data silo is an isolated repository, often structured, not designed for raw data storage.
* Data mart (Option C): A data mart is a subset of a data warehouse, also storing structured data.
* Data lake (Option D): A data lake stores raw, unformatted data in its original format(structured, semi- structured, or unstructured), making it the correct choice.
The DA0-002 Data Concepts and Environments domain includes understanding "different types of databases and data repositories," and a data lake is designed for raw data storage.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.
NEW QUESTION # 104
Which of the following allows a data analyst to send out a spreadsheet containing sensitive information without revealing personal details?
Answer: C
NEW QUESTION # 105
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