
Data analyst project - quick turn around
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- Proposals: 33
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Top rated Data Analyst | Power BI & Excel Guru | SPSS Expert | Data Analysis |Data Visualization Expert

Multidisciplinary Designer and Developer, Creative Content Data Entery, and Business Support Specialist
Tableau Specialist| Data Analyst | SQL | PowerBI | Excel (&VBA) - Passionate about *effective * data visualization

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Description
Experience Level: Entry
Description:
The project involves reviewing student response data from a school wellbeing survey, drawing insights, making comparisons, creating tables, graphs, pie charts, and explaining the data's implications for school wellbeing and the student experience. The freelancer will review the data, identify patterns, and create visual representations to effectively communicate the findings. The project requires expertise in data analysis, visualization, and communication. The freelancer will work with the provided data set and remove sensitive details (name and email address). An example of the sheet is attached.
for school audience NOT boardroom
The project involves reviewing student response data from a school wellbeing survey, drawing insights, making comparisons, creating tables, graphs, pie charts, and explaining the data's implications for school wellbeing and the student experience. The freelancer will review the data, identify patterns, and create visual representations to effectively communicate the findings. The project requires expertise in data analysis, visualization, and communication. The freelancer will work with the provided data set and remove sensitive details (name and email address). An example of the sheet is attached.
for school audience NOT boardroom
R C.
98% (11)Projects Completed
11
Freelancers worked with
12
Projects awarded
37%
Last project
21 Jan 2025
United Arab Emirates
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Log inClarification Board Ask a Question
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1.What specific aspects of student wellbeing are you most interested in analyzing?
2.Are there any particular visual formats you prefer for the data presentation (e.g., specific graph types)?
3.Is there a preferred method for delivering the final report (PDF, presentation, etc.)?
4.Are there any additional datasets or context that should be considered during the analysis?
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Besides removing names and email addresses, are there other data-cleaning tasks required (e.g., handling missing values, duplicates, or anomalies)?
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