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| Section | Weight | Objectives |
|---|---|---|
| Data Acquisition and Preparation | 22% | - Data extraction, transformation, and loading (ETL/ELT) - Data cleaning, validation, and quality improvement - Data collection methods and sources - Data integration and normalization |
| Data Governance, Quality, and Management | 14% | - Data governance frameworks and policies - Data privacy, security, and compliance - Data lifecycle management and documentation - Data quality standards and monitoring |
| Visualization and Reporting | 20% | - Dashboard and report development - Validation and accuracy of reports - Communicating insights to stakeholders - Design principles for effective visualizations |
| Data Concepts and Environments | 20% | - Foundational concepts of AI and machine learning in data - Database systems and architectures - Data types, structures, and formats - Cloud and distributed data environments |
| Data Analysis | 24% | - Analytical tools and querying languages - Statistical methods and techniques - Exploratory and confirmatory data analysis - Data modeling and pattern recognition |
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NEW QUESTION # 203
A sales manager wants to understand how sales are trending year over year. Which of the following chart types is the most appropriate to display the information?
Answer: D
NEW QUESTION # 204
A table contains several rows of cellular numbers with call timestamps, call durations, called numbers, and carriers of the called number. Which of the following allows a data analyst to sort the cellular numbers based on the carriers of the called numbers and include the total call durations?
Answer: B
Explanation:
Grouping by both cellular number and called number carrier allows aggregation of total call duration per combination, and ordering by the carrier sorts the results as required.
NEW QUESTION # 205
A data analyst must combine service calls into low-, medium-, and high-priority levels in order to analyze organizational responses. Which of the following techniques should the analyst use for this task?
Answer: C
Explanation:
Binning groups values into defined categories, such as low, medium, and high priority levels, enabling structured analysis of service call responses.
NEW QUESTION # 206
A data analyst needs to create and deliver a dashboard that displays the company's financial transactions as they are updated. Which of the following delivery methods should the analyst consider? (Select two).
Answer: D,F
Explanation:
This question is part of theVisualization and Reportingdomain, focusing on delivery methods for dashboards. The requirement for displaying financial transactions "as they are updated" implies a need for real-time updates and interactivity, which narrows down the options.
* Real-time (Option A): Real-time delivery ensures the dashboard reflects the latest data as transactions are updated, meeting the requirement.
* Snapshot (Option B): A snapshot provides a static view at a specific point, not suitable for ongoing updates.
* Dynamic (Option C): A dynamic dashboard allows for interactivity and can be updated as data changes, complementing real-time delivery.
* Static (Option D): Static dashboards don't update automatically, making this incorrect.
* Ad hoc (Option E): Ad hoc delivery is for one-time reports, not ongoing updates.
* Time series (Option F): Time series refers to a data type or visualization, not a delivery method.
The DA0-002 Visualization and Reporting domain includes understanding "the appropriate visualization in the form of a report or dashboard" with delivery methods Real-time and dynamic methods best support the need for updated financial transaction dashboards.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization andReporting
NEW QUESTION # 207
A company experiences a data breach that exposes some customers' information. A data analyst must categorize the customer data into fully affected, partially affected, and not affected. Which of the following is the best technique to use to quantify the extent of the breach?
Answer: B
Explanation:
Binning groups data into predefined categories or ranges. Classifying customers as fully affected, partially affected, and not affected is a form of binning that enables the analyst to quantify and measure the extent of the breach by placing records into meaningful categories.
NEW QUESTION # 208
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