DA0-001 Exam Dumps - CompTIA Data+ Certification Exam

Discrete data is a type of data that can only take certain values, usually whole numbers or integers. Discrete data can be counted, but not measured. For example, the number of students in a class, the number of books in a library, or the number of phone calls that a call center receives in a day are all examples of discrete data. Discrete data is different from continuous data, which can take any value within a range, and can be measured with precision. For example, the height of a person, the weight of a fruit, or the temperature of a room are all examples of continuous data. Therefore, the correct answer is D. References: [Discrete vs Continuous Data: Definition and Examples - Statistics How To], [Discrete Data - Definition and Examples | Math Goodies]

Gross profit percentage is a key performance indicator (KPI) that measures the profitability of a company’s sales by showing the percentage of revenue that exceeds the cost of goods sold (COGS). It is a critical metric for tracking sales performance because it directly reflects the efficiency of a company in managing its production costs and the profitability of its products. This KPI is essential for understanding the financial health of a business and making informed decisions about pricing, cost control, and sales strategies.

References:

Sales KPIs are essential for measuring the effectiveness of sales activities and the profitability of those efforts1.

Gross profit percentage is highlighted as a crucial metric for assessing the financial success of sales initiatives2.

Understanding the difference between sales metrics and KPIs, and the importance of gross profit percentage as a KPI1.

The significance of gross profit percentage in evaluating sales team performance and guiding business decisions3.

A pie chart is the best choice to show the composition between the categories of the survey response data set. A pie chart represents the whole with a circle, divided by slices into parts. Each slice shows the relative size of each category as a percentage of the total. A pie chart is useful when the categories are mutually exclusive and add up to 100%. The table shows the favorite color and the number of responses for each color, which can be easily converted into percentages. A pie chart can show how each color contributes to the total number of responses.

Option A is incorrect because a histogram is used to show how data points are distributed along a numerical scale. The survey response data set is not numerical, but categorical.

Option C is incorrect because a line chart is used to show trends or changes over time. The survey response data set does not have a time dimension.

Option D is incorrect because a scatter plot is used to show the relationship between two numerical variables. The survey response data set does not have two numerical variables.

Option E is incorrect because a waterfall chart is used to show how an initial value is increased or decreased by a series of intermediate values. The survey response data set does not have an initial value or intermediate values.

References:

How to Choose the Right Chart for Your Data - Infogram

How to Choose the Right Data Visualization | Tutorial by Chartio

Find the Best Visualizations for Your Metrics - The Data School

How to choose the best chart or graph for your data

The option that the data analyst should use to best communicate the information to the manager is a summary with statistics, conclusions, and recommendations from the data analyst. A summary is a concise and clear way of presenting the main findings and insights from the data analysis report. A summary should include relevant statistics that support the conclusions and recommendations from the data analyst. A summary should also highlight the most important KPIs and measure the return on marketing investment in relation to the objectives of the online marketing campaign. The other options are not as effective as using a summary to communicate the information to the manager, as they either provide too much or too little information or do not address the manager’s needs or expectations. A real-time monitor may provide too much information that can be overwhelming or distracting for the manager who wants to see only the most important KPIs and measure the return on marketing investment. A self-service dashboard may provide too little information that can be insufficient or unclear for the manager who wants to see some guidance and interpretation from the data analyst. A spreadsheet of raw data may provide irrelevant or inaccurate information that can be confusing or misleading for the manager who wants to see some analysis and insights from the data analyst. Reference: [How to Write an Executive Summary for Your Data Analysis Report - Towards Data Science]

Explanation

The correct answer is B: Derived variables Derived variables are variables that you create by calculating or categorizing variables that already exist in your data set.

Data merge is incorrect. Data merging is the process of combining two or more data sets into a single data set. Data blending is incorrect.

Data blending involves pulling data from different sources and creating a single, unique, dataset for visualization and analysis.

Data append is incorrect. A data append is a process that involves adding new data elements to an existing database.

Comprehensive and Detailed In-Depth Explanation:

When undertaking the task of revamping a long-standing company-wide dashboard, it's imperative to begin by understanding the specific needs and objectives of the stakeholders who requested the update. This ensures that the revamped dashboard aligns with current business requirements and provides relevant insights.

Option A:Talk to the group that made the request to determine the desired goal.

Rationale:Engaging with the requesting group allows the analyst to gather detailed information about their expectations, the challenges they face with the current dashboard, and the specific metrics or data visualizations they require. This collaborative approach ensures that the final product is user-centric and meets the actual needs of its users.