CompTIA DA0-002 Practice Test Questions Answers

This question pertains to theVisualization and Reportingdomain, focusing on selecting the appropriate communication method for a report. The requirements emphasize simplicity, clarity, accessibility, and automatic updates, which point to a specific approach.

Executive summary (Option A): An executive summary is a written document that summarizes metrics but isn’t typically updated automatically and may not be accessible toall levels without distribution.

Slide presentation (Option B): A slide presentation can be clear but requires manual updates and isn’t inherently accessible to all company levels.

Key performance indicator dashboard (Option C): A KPI dashboard provides a simple, visual summary of metrics, is clear and concise, can be understood by all levels, and can be set up to update automatically, meeting all requirements.

Open data portal (Option D): An open data portal provides raw data access, which may not be simple or easily understood by all levels.

The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a KPI dashboard is the best approach for meeting these requirements.

This question pertains to theData Acquisition and Preparationdomain, focusing on combining data from two tables. Both tables have the same structure (ID, First_name, Last_name, Job_title) and contain employee data, suggesting the task is to create a single list of all employees.

Group (Option A): Grouping (e.g., GROUP BY in SQL) is for aggregation (e.g., counting employees by job title), not combining tables into a single report.

Join (Option B): Joining tables (e.g., INNER JOIN) requires a common key and combines tables horizontally, but there’s no indication of a relationship between the tables (e.g., no shared key beyond ID, which isn’t linked).

Union (Option C): UNION combines the rows of two tables with the same structure into a single result set, removing duplicates, which is ideal for creating a combined report of all employees from both tables.

Nested (Option D): Nested queries (e.g., subqueries) are used for complex filtering, not for combining tables into a single list.

The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," and UNION is the best method for combining two tables with identical structures into a single report.

This question falls under theVisualization and Reportingdomain of CompTIA Data+ DA0-002, which involves understanding the components necessary for designing a report. The given requirements cover data, visuals, and design, but a key aspect of report planning is missing.

Source validation (Option A): Source validation ensures data accuracy, but it’s typically part of the data preparation phase, not a report design requirement.

Design elements (Option B): Color branding, labels, and terminology are design elements, so this is already included.

Delivery method (Option C): The delivery method (e.g., recurring, ad hoc, self-service) specifies how the report will be distributed or accessed, which is a critical requirement missing from the list.

Report type (Option D): Suggested charts and tables imply the report type (e.g., summary, dashboard), so this is indirectly covered.

The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and the delivery method is a key component of report planning that’s missing here.

This question pertains to theData Governancedomain, focusing on data quality and report performance optimization. The report is slow despite no technical issues, suggesting a data-related inefficiency.

Check that the appropriate filters are applied (Option A): Applying filters reduces the dataset size by excluding irrelevant data, improving report performance. This is a logical next step after ruling out technical issues.

Check data source connections (Option B): The analyst already reviewed the system and found no operational issues, so connectivity is likely not the problem.

Check for data structure changes in the report (Option C): While possible, this is a deeper investigation step and less likely to be the immediate cause of slowness.

Check whether other peers have the same issue (Option D): This might confirm the issue’s scope but doesn’t directly address the performance problem.

The DA0-002 Data Governance domain emphasizes "data quality control concepts," including optimizing report performance through techniques like filtering.

This question pertains to theData Acquisition and Preparationdomain, which in DA0-002 includes understanding data acquisition concepts and the types of data gathered from varioussources, such as web scraping. Web scraping involves extracting data from websites, and the data gathered is often semi-structured, meaning it has some organizational structure but isn’t fully relational like a database table.

JSON (Option A): JSON (JavaScript Object Notation) is a semi-structured data format commonly used in web applications. Web scraping often retrieves data in JSON format via APIs or embedded scripts, as it’s lightweight and structured with key-value pairs, making it ideal for semi-structured data.

CSV (Option B): CSV (Comma-Separated Values) is a structured format typically used for tabular data. It’s not commonly the direct output of web scraping, though scraped data might be converted to CSV later.

CSS (Option C): CSS (Cascading Style Sheets) is used for styling web pages and isn’t a data format, making it irrelevant for describing scraped data.

HTML (Option D): HTML (HyperText Markup Language) is the structure of web pages and is often the raw format scraped during web scraping. While HTML is semi-structured due to its tag-based hierarchy, it’s primarily a markup language, not a data format, and the actual data extracted is often parsed into formats like JSON.

The DA0-002 Data Acquisition and Preparation domain aligns with the DA0-001 focus on "data acquisition concepts" (web ID: 14), which includes identifying formats like JSON as semi-structured data commonly acquired through web scraping. JSON is the best fit here due to its prevalence in web data exchange.