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| Section | Weight | Objectives |
|---|---|---|
| Data Acquisition and Preparation | 22% | - Data cleaning, validation, and quality improvement - Data collection methods and sources - Data integration and normalization - Data extraction, transformation, and loading (ETL/ELT) |
| Visualization and Reporting | 20% | - Communicating insights to stakeholders - Dashboard and report development - Design principles for effective visualizations - Validation and accuracy of reports |
| Data Concepts and Environments | 20% | - Cloud and distributed data environments - Database systems and architectures - Data types, structures, and formats - Foundational concepts of AI and machine learning in data |
| Data Analysis | 24% | - Data modeling and pattern recognition - Exploratory and confirmatory data analysis - Statistical methods and techniques - Analytical tools and querying languages |
| 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 |
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NEW QUESTION # 149
The human resources department wants to understand the relationship between the ages and incomes of all employees. Which of the following graphics is the most appropriate to present the analysis?
Answer: C
Explanation:
A scatter plot is used to visualize the relationship between two numerical variables, such as age and income, allowing patterns or correlations to be identified.
NEW QUESTION # 150
An analyst is building a reporting deck. The deck must include tracking and visualizing metrics and row-level security. Which of the following actions should the analyst take after meeting all of the requirements?
Answer: C
NEW QUESTION # 151
A data analyst is creating a forecast for a product line introduced early last year. Which of the following should the analyst use to create projected sales and customer satisfaction for next year?
Answer: A
Explanation:
This question pertains to theData Analysisdomain, focusing on data types and methods for forecasting. The task involves projecting sales (numerical) and customer satisfaction (likely ordinal,e.g., ratings), requiring appropriate data attributes.
* Standard deviation and constraints (Option A): Standard deviation measures data spread, and constraints are conditions, neither of which directly supports forecasting.
* Mean and median (Option B): Mean and median are descriptive statistics, not sufficient for forecasting future values.
* Boolean data and an array (Option C): Boolean data (true/false) and arrays (data structures) are not relevant for forecasting sales and satisfaction.
* Numerical and ordinal attributes (Option D): Sales are numerical (e.g., units sold), and customer satisfaction is often ordinal (e.g., 1-5 ratings). These attributes are suitable for forecasting models (e.g., time-series analysis for sales, regression for satisfaction).
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and numerical and ordinal attributes are key for forecasting sales and satisfaction.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
NEW QUESTION # 152
Which of the following data integration concepts should be used if only new data is being added to a table since the previous load?
Answer: A
Explanation:
Delta load refers to loading only the new or changed data since the last update, optimizing data integration processes.
NEW QUESTION # 153
The sales department wants to include the composition of total sales amounts across all three sales channels in a report. Given the following sample sales table:
Sales channel
Month
Sales (million $)
Digital
January
135
Store
February
145
Online
March
165
Store
April
200
Store
May
125
Online
June
155
Digital
July
120
Online
August
145
Digital
September
160
Which of the following visualizations is the most appropriate?
Answer: B
Explanation:
This question pertains to theVisualization and Reportingdomain, focusing on selecting the appropriate visualization for a specific requirement. The task is to show the composition of total sales across three channels, which involves showing proportions.
* Pivot table (Option A): A pivot table summarizes data but isn't a visualization; it's more for data exploration.
* Pie chart (Option B): A pie chart shows the proportion of total sales for each channel (Digital, Store, Online), which is ideal for displaying composition.
* KPI card (Option C): A KPI card displays a single metric, not suitable for showing composition across multiple channels.
* Box plot (Option D): A box plot shows data distribution (e.g., quartiles), not proportions.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and a pie chart is best for showing the composition of totals.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.
NEW QUESTION # 154
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