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| Topic 1 | - Data Concepts and Environments: This section of the exam measures the skills of a Junior Data Analyst and focuses on understanding core data concepts such as database types, schema structures, and data formats. It highlights differences between structured and unstructured data, compares file types like CSV, JSON, and XML, and introduces key ideas about data dimensions and slowly changing dimensions. Knowing how data is stored and organized helps professionals better prepare for analysis and reporting tasks.
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| Topic 2 | - Data Mining: This section of the exam measures skills of a Business Intelligence Analyst and covers how data is collected, cleaned, and prepared for analysis. It explains methods like ETL and ELT for data integration, as well as web scraping, API use, and survey data collection. Candidates are expected to identify issues like missing or duplicated data and apply techniques like filtering, sorting, merging, and normalizing. The section also touches on query optimization strategies to improve data handling efficiency.
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| Topic 3 | - Visualization: This section of the exam measures skills of a Data Visualisation Specialist and focuses on turning raw data into clear, visual insights. It teaches how to match visual formats like bar charts, heat maps, and line graphs to specific audiences and needs. Candidates must understand how to create dashboards and reports using proper design elements such as labels, layout, branding, and colour schemes. This section also includes best practices for dashboard development and delivery through various platforms and user access levels.
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CompTIA Data+ Exam Sample Questions (Q171-Q176):
NEW QUESTION # 171
A data analyst needs to access data from the last ten years to develop a report. Which of the following should the analyst do to develop the report without affecting the system's performance?
- A. Connect to the production database and create a query that retrieves only the required data
- B. Download data from each month as independent flat files and create a local repository for further review
- C. Restore annual backups of the database in a local computer and query the current year's data in production
- D. Create a snapshot of the selected period and work on the data analysis in an isolated environment
Answer: D
Explanation:
Creating a snapshot of the required historical data and performing the analysis in an isolated environment allows the analyst to work with the necessary ten years of data without placing additional load on the production system. This approach minimizes the impact on system performance while providing a stable dataset for reporting and analysis.
NEW QUESTION # 172
A data analyst is creating a pivot table for a large dataset for an upcoming board meeting. Which of the following is the purpose of the pivot table?
- A. To retrieve and clean data from several sources
- B. To visualize the data in a dashboard
- C. To organize the data for reporting
- D. To summarize and analyze the data
Answer: D
Explanation:
This question pertains to theData Analysisdomain, focusing on the purpose of a pivot table. Pivot tables are a tool for summarizing and analyzing data, often used in preparation for reporting.
* To visualize the data in a dashboard (Option A): Pivot tables summarize data but aren' tvisualizations; charts in dashboards might be created from pivot tables.
* To retrieve and clean data from several sources (Option B): Retrieving and cleaning data is part of data preparation, not the purpose of a pivot table.
* To summarize and analyze the data (Option C): Pivot tables aggregate and summarize data (e.g., by calculating sums, averages) and allow for analysis (e.g., filtering, grouping), which is their primary purpose.
* To organize the data for reporting (Option D): While pivot tables can help organize data, their main purpose is summarization and analysis, not just organization.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and pivot tables are a key tool for summarizing and analyzing large datasets.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
NEW QUESTION # 173
An analyst compiled data on the preferred color of various models of cars over a period of time.
Which of the following visualizations is best way to present this information?
- A. Heat map
- B. Line graph
- C. Bubble chart
- D. Stacked chart
Answer: D
Explanation:
A stacked chart effectively displays the distribution of categories (car colors) across different models over time, showing proportions and comparisons.
NEW QUESTION # 174
A data analyst is evaluating all conditions in a query. Which of the following is the best logical function to accomplish this task?
Answer: B
Explanation:
AND requires all specified conditions in a query to be true, making it the appropriate logical function when evaluating all conditions together.
NEW QUESTION # 175
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?
- A. Binning
- B. Augmentation
- C. Scaling
- D. Imputation
Answer: A
Explanation:
Binning groups values into defined categories, such as low, medium, and high priority levels, enabling structured analysis of service call responses.
NEW QUESTION # 176
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