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| Section | Weight | Objectives |
|---|---|---|
| Data Governance, Quality, and Controls | 15% | - Compliance, privacy, and security controls - Data quality management - Data governance frameworks and policies |
| Data Mining | 25% | - Data processing and transformation - Data manipulation and cleaning techniques - Data collection and extraction methods |
| Data Analysis | 25% | - Data interpretation and reporting - Statistical methods and analysis techniques - Trend and pattern identification |
| Visualization | 20% | - Visualization best practices - Chart and dashboard design principles - Data storytelling and reporting tools |
| Data Concepts and Environments | 15% | - Data storage systems and platforms - Data lifecycle and data ecosystems - Data types, structures, and file formats |
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NEW QUESTION # 150
A database administrator is attempting to load a set of database logs into a software system.
Upon processing the data, the administrator receives a notification that this process failed because the data size is too large for the system memory. Which of the following is the best way for the administrator to correct this issue?
Answer: A
Explanation:
Chunking processes large data sets in smaller, manageable pieces, allowing the system to handle the data without exceeding memory limits.
NEW QUESTION # 151
Which of the following elements is the most important to include in a dashboard for internal technical audiences?
Answer: D
Explanation:
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.
NEW QUESTION # 152
A data analyst is analyzing the following dataset:
Which of the following methods should the analyst use to determine the total cost for each transaction?
Answer: A
Explanation:
Deriving creates a new value from existing fields, such as calculating total cost by multiplying quantity by item price for each transaction.
NEW QUESTION # 153
A data analyst wants to use the following tables to find all the customers who have not placed an order:
Customers table
ID
Name
Address
Products table
ID
Name
Customer_ID
Which of the following SQL statements is the best way to accomplish this task?
Answer: C
Explanation:
This question pertains to theData Analysisdomain, focusing on SQL queries to analyze data relationships.
The task is to find customers who have not placed an order, meaning customers in the Customers table without a matching Customer_ID in the Products table.
* Option A: SELECT * FROM CUSTOMERS AS C LEFT JOIN PRODUCTS AS P ON C.ID = P.
Customer_ID WHERE P.Customer_ID IS NULLA LEFT JOIN includes all customers, even those without orders (where Products columns are NULL). Filtering with WHERE P.Customer_ID IS NULL selects only customers without a match in Products, correctly identifying those who haven't ordered.
* Option B: SELECT * FROM CUSTOMERS AS C INNER JOIN PRODUCTS AS P ON C.ID = C.
ID WHERE COUNT(P.*) = 0An INNER JOIN only includes matching records, so it won't return customers without orders. The join condition C.ID = C.ID is also incorrect, and COUNT requires a GROUP BY, making this invalid.
* Option C: SELECT * FROM PRODUCTS AS P INNER JOIN CUSTOMERS AS C ON P.
Customer_ID = C.ID WHERE (SELECT COUNT(P.*) = 0)An INNER JOIN excludes customers without orders, and the subquery syntax is incorrect (COUNT needs a GROUP BY or to be part of a HAVING clause).
* Option D: SELECT * FROM PRODUCTS AS P LEFT JOIN CUSTOMERS AS C ON P.
Customer_ID = C.ID WHERE P.Customer_ID IS NOT NULLThis starts with Products and joins Customers, returning only records with orders (opposite of the task), and IS NOT NULL further excludes non-ordering customers.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and a LEFT JOIN with a NULL check is the standard method for finding non-matching records.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
NEW QUESTION # 154
A data analyst is modeling a new data warehouse to analyze sales. One of the requirements is to analyze sales by region. Which of the following best describes the region table?
Answer: D
Explanation:
A region table provides descriptive attributes used to categorize and analyze facts such as sales, which makes it a dimension table in a data warehouse schema.
NEW QUESTION # 155
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