A data analyst needs to join together a table data source and a web API data source using Python. Which of the following is the best way to accomplish this task?
Correct Answer:
B
This question falls under theData Acquisition and Preparationdomain of CompTIA Data+ DA0-002, which involves acquiring and combining data from different sources, such as a database and a web API, using tools like Python. The task requires joining the data, which in Python often involves using pandas DataFrames.
✑ Convert the data from the API and database to a varchar format and convert them to pandas DataFrames that are then merged together (Option A): VARCHAR is a databasedata type for strings, not a format for data exchange or merging in Python, making this incorrect.
✑ Convert the data from the API and database to a JSON format and convert them to pandas DataFrames that are then merged together (Option B): Web APIs commonly return data in JSON format, and databases can export data as JSON. In Python, JSON data can be easily converted to pandas DataFrames using pandas.read_json() or pandas.DataFrame(), and then merged using pandas.merge() on a common key, making this the best approach.
✑ Convert the data from the API and database to a TXT format and convert them topandas DataFrames that are then merged together (Option C): TXT is a generic text format that lacks structure, making it less efficient for merging compared to JSON.
✑ Convert the data from the API and database to a string format and convert them to pandas DataFrames that are then merged together (Option D): Converting to a string format is vague and not a standard approach for structured data merging in Python.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as combining data from APIs and databases, and JSON is a standard format for this purpose in Python.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.
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Which of the following elements is the most important to include in a dashboard for internal technical audiences?
Correct Answer:
C
This question pertains to theVisualization and Reportingdomain, focusing on dashboard design for specific audiences. Internal technical audiences (e.g., data analysts, IT staff) need actionable, data-driven insights.
✑ Methodology section (Option A): Methodology is important for research reports,
not dashboards, especially for technical audiences who prioritize data.
✑ Dynamic features (Option B): Dynamic features (e.g., interactivity) are useful but not the most critical element for technical audiences.
✑ Key performance indicators (Option C): KPIs provide critical metrics (e.g., system uptime, error rates) that technical audiences need to monitor and act on, making this the most important element.
✑ Company branding (Option D): Branding is more relevant for external audiences, not internal technical ones.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and KPIs are essential for technical dashboards.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.
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A data analyst is following up on a recent, company-wide data audit of customer invoice data. Which of the following is the best option for the analyst to use?
Correct Answer:
B
This question falls under theData Governancedomain of CompTIA Data+ DA0-002, which includes understanding compliance frameworks for data audits, especially for customer data. The scenario involves a data audit of customer invoice data, which likely contains personal information, making privacy regulations relevant.
✑ PCI DSS (Option A): PCI DSS (Payment Card Industry Data Security Standard)
applies specifically to payment card data, not general customer invoice data unless credit card details are involved, which isn??t specified.
✑ GDPR (Option B): GDPR (General Data Protection Regulation) is a
comprehensive privacy regulation for handling personal data of EU citizens, including customer invoice data, which may contain PII like names and addresses. It??s the most relevant for a company-wide data audit.
✑ ISO (Option C): ISO standards (e.g., ISO 27001) relate to information security
management but are not specific to customer data privacy audits.
✑ PII (Option D): PII (Personally Identifiable Information) is a concept, not a framework or tool for conducting an audit.
The DA0-002 Data Governance domain emphasizes "identifying PII and data privacy concepts," and GDPR is the most appropriate framework for auditing customer data to ensure compliance with privacy laws.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.
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A data analyst needs to create a combined report that includes information from the following two tables:
Managers table
ID
First_name Last_name Job_title 1001
John Doe Manager 1002
Jane Roe Director
Non-managers table ID
First_name Last_name Job_title 1003
Robert Roe
Business Analyst 1004
Jane Doe
Sales Representative 1005
John Roe
Operations Analyst
Which of the following query methods should the analyst use for this task?
Correct Answer:
C
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.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.
Which of the following data repositories stores unstructured and structured data?
Correct Answer:
D
This question falls under theData Concepts and Environmentsdomain of CompTIA Data+ DA0-002, which involves understanding different types of data repositories and their characteristics. The task is to identify a repository that can store both unstructured and structured data.
✑ Data store (Option A): A data store is a general term for any data repository, but
it??s not specific enough to confirm it stores both unstructured and structured data.
✑ Data silo (Option B): A data silo is an isolated data repository, often structured, and not typically designed for unstructured data.
✑ Data mart (Option C): A data mart is a subset of a data warehouse, focused on structured data for specific business areas, not unstructured data.
✑ Data lake (Option D): A data lake is a centralized repository that stores raw data in its native format, including both structured (e.g., tables) and unstructured (e.g., text, images) data, 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 specifically designed to handle both unstructured and structured data.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.
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