Data Analyst Professional Practical Exam Submission
You can use any tool that you want to do your analysis and create visualizations. Use this template to write up your summary for submission.
You can use any markdown formatting you wish. If you are not familiar with Markdown, read the Markdown Guide before you start.
📝 Task List
Your written report should include written text summaries and graphics of the following:
- Data validation:
- Describe validation and cleaning steps for every column in the data
- Exploratory Analysis:
- Include two different graphics showing single variables only to demonstrate the characteristics of data
- Include at least one graphic showing two or more variables to represent the relationship between features
- Describe your findings
- Definition of a metric for the business to monitor
- How should the business use the metric to monitor the business problem
- Can you estimate initial value(s) for the metric based on the current data
- Final summary including recommendations that the business should undertake
Start writing report here..
Data Analyst Professional Practical Exam Submission
Business Goal
The company wants to understand its revenue patterns and optimize its sales strategy. This analysis aims to uncover trends in revenue, sales methods, and customer behavior to guide data-driven decision-making.
Data Validation
Cleaning and Validation Steps
Sales Method:
Standardized inconsistent values (e.g., 'email' → 'Email', 'em + call' → 'Email + Call'). Converted to a categorical data type for consistency. Rationale: Ensures uniformity in analysis and prevents duplicate categories from distorting results.
Revenue:
Identified 1,074 missing values and filled them with the median revenue. Rationale: The median prevents extreme values from skewing the data while maintaining realistic revenue estimates.
Customer ID:
Verified as a unique identifier, not relevant for analysis. Rationale: This column does not provide analytical value beyond record-keeping.
State:
Verified as categorical, ensuring correct data classification. Rationale: Ensuring consistency for potential geographical insights.
Duplicates:
No duplicate rows found, confirming data integrity. Rationale: Prevents double counting of sales records.
Exploratory Analysis
Single Variable Insights
Revenue Distribution:
Visualized using a histogram.
Insight:
The data is skewed to the right, meaning most transactions are lower in value, with fewer high-revenue transactions.
Business Implication:
The company should focus on increasing high-value sales.
Sales Method Distribution:
Visualized using a bar chart.
Insight:
The majority of sales occur through Email, followed by Email + Call, and then Call.
Business Implication:
Email is the dominant method, but a mix of Email and Calls may yield better revenue per transaction.
Multivariable Insights
Revenue vs. Number of Products Sold:
Visualized using a scatterplot.
Insight:
There is a positive correlation between revenue and the number of products sold, but some low-sales transactions generate high revenue, indicating possible high-value products.
Business Implication:
The company should analyze high-value transactions to identify premium products or pricing strategies.
Business Metric: Customer Lifetime Value (CLV)
Definition:
CLV = Average Revenue per Customer × Average Years as a Customer
Estimated CLV:
$464.90 based on current data.
How the Business Should Use CLV:
Identifies high-value customers to prioritize retention efforts. Optimizes sales strategies by focusing on the most profitable acquisition channels. Supports personalized marketing to maximize revenue per customer.
Final Summary & Recommendations
Increase Customer Retention:
Implement loyalty programs and personalized marketing strategies to extend customer relationships. Rationale: Retaining customers is more cost-effective than acquiring new ones.
Optimize Sales Methods:
While Email generates the most sales, the Email + Call method should be further explored for its potential to drive higher revenue per transaction. Rationale: Combining communication channels may lead to higher engagement and conversions.
Focus on High-Value Customers:
Analyze characteristics of top revenue-generating customers and tailor marketing efforts toward similar profiles. Rationale: Prioritizing high-value customers can increase overall profitability.
Monitor CLV Regularly:
Track CLV over time to adjust sales strategies and improve customer retention efforts. Rationale: Keeping an eye on CLV helps refine marketing and sales approaches to sustain long-term revenue growth.
✅ When you have finished...
- Publish your Workspace using the option on the left
- Check the published version of your report:
- Can you see everything you want us to grade?
- Are all the graphics visible?
- Review the grading rubric. Have you included everything that will be graded?
- Head back to the Certification Dashboard to submit your practical exam report and record your presentation