Capstone Project 8-A

End-to-End Data Analytics Project

Demonstrate your mastery of data analytics by building a complete end-to-end analytics project. From data collection and analysis to visualization and dashboard creation - showcase everything you have learned throughout this course in one comprehensive portfolio project.

15-25 hours
Advanced
500 Points
Submit Project
Skills Demonstrated
  • Data collection and preparation
  • Excel and SQL analysis
  • Statistical analysis
  • Python data processing
  • Power BI/Tableau dashboards
  • Business insights and recommendations
Contents
01

Project Overview

The Final Project is your opportunity to showcase everything you have learned in this Data Analytics course. You will build a complete, end-to-end analytics project that can be added to your professional portfolio. This project should demonstrate your ability to solve real-world business problems using data analytics techniques.

Portfolio-Ready: This project is designed to be impressive enough to show potential employers. Take your time, document everything thoroughly, and create something you are proud of!
Full Course Integration: This project integrates concepts from ALL modules: Excel fundamentals, SQL queries, statistical analysis, Power BI/Tableau dashboards, Python analytics, and business storytelling.
Excel & SQL

Data manipulation, queries, and pivot tables

Visualization

Power BI, Tableau, or Python charts

Statistics

Descriptive stats, hypothesis testing

Business Insights

Recommendations and storytelling

Ready to submit? Already completed your project? Submit your work now!
Submit Now
02

Project Options

Choose ONE of the following project tracks. Each track presents a unique challenge and allows you to specialize in a specific area of data analytics.

Option A: Sales Analytics Dashboard

Build a comprehensive sales analytics solution that tracks performance, identifies trends, and provides actionable insights for sales teams. Analyze revenue, products, regions, and customer segments.

Suggested Datasets
  • Superstore Sales Dataset (Kaggle)
  • E-Commerce Sales Data
  • Retail Transaction Dataset
  • AdventureWorks Sales Data
Required Analysis
  • Revenue trends and forecasting
  • Product performance analysis
  • Regional sales comparison
  • Customer segmentation insights

Option B: Financial Analytics Report

Create a financial analysis dashboard that provides insights into company performance, budgeting, and financial health. Include profitability analysis, expense tracking, and KPI monitoring.

Suggested Datasets
  • Company Financial Statements
  • Budget vs Actuals Data
  • Stock Market Data (Yahoo Finance)
  • Bank Transaction Dataset
Required Analysis
  • Profit and loss analysis
  • Budget variance reporting
  • Cash flow visualization
  • Financial ratio calculations

Option C: HR Analytics Platform

Build an HR analytics solution that analyzes workforce data, tracks employee metrics, and identifies patterns in attrition, performance, and engagement.

Suggested Datasets
  • IBM HR Analytics Dataset
  • Employee Performance Data
  • Recruitment Pipeline Data
  • Workforce Demographics Dataset
Required Analysis
  • Attrition pattern analysis
  • Employee demographics breakdown
  • Performance distribution study
  • Compensation equity analysis

Option D: Custom Analytics Project

Have your own project idea? Build something unique that demonstrates your data analytics skills. Custom projects must be pre-approved by submitting a brief proposal.

Approval Required: If choosing Option D, email your project proposal (1 paragraph describing the problem, dataset, and approach) before starting. Custom projects must meet the same complexity requirements as Options A-C.
03

Technical Requirements

Regardless of which project option you choose, your project must include ALL of the following components:

1
Data Collection and Preparation
  • Use a dataset with at least 5,000 rows and 10+ columns
  • Document the data source clearly (Kaggle, public APIs, etc.)
  • Perform thorough data cleaning (handle missing values, duplicates, outliers)
  • Include a data dictionary explaining each column
2
Exploratory Data Analysis (EDA)
  • Statistical summary of all key metrics
  • At least 8 meaningful visualizations (charts, graphs, heatmaps)
  • Trend analysis and pattern identification
  • Clear insights documented with business context
  • Data quality assessment and profiling
3
SQL Analysis
  • Write at least 10 SQL queries demonstrating various techniques
  • Include JOINs, aggregations, subqueries, and window functions
  • Document each query with business question it answers
  • Export query results for dashboard use
4
Statistical Analysis
  • Calculate key descriptive statistics
  • Perform at least one hypothesis test relevant to your data
  • Create correlation analysis between key variables
  • Document statistical findings with business interpretation
5
Interactive Dashboard (Power BI or Tableau)
  • Create a multi-page dashboard with at least 4 pages
  • Include KPI cards, charts, tables, and filters
  • Implement interactivity (slicers, drill-through, tooltips)
  • Apply consistent formatting and professional design
  • Add navigation between dashboard pages
6
Python Analysis (Optional but Recommended)
  • Use pandas for data manipulation and cleaning
  • Create visualizations with matplotlib or seaborn
  • Perform advanced analysis not easily done in Excel
  • Document code in Jupyter notebooks with markdown explanations
7
Business Recommendations
  • Provide at least 5 actionable recommendations
  • Support each recommendation with data evidence
  • Create an executive summary (1-2 pages)
  • Discuss limitations and future analysis opportunities
04

Deliverables

Your final submission must include all of the following files in your Google Drive folder:

Folder Structure
Data-Analytics-Final-Project-[YourName]/
├── README.md                      # Project overview, setup instructions, key findings
├── data/
│   ├── raw/                       # Original, unprocessed data files
│   └── processed/                 # Cleaned and transformed data
├── sql/
│   └── queries.sql                # All SQL queries with comments
├── excel/
│   └── analysis.xlsx              # Excel analysis with pivot tables
├── notebooks/
│   ├── 01_data_exploration.ipynb  # EDA notebook (if using Python)
│   └── 02_analysis.ipynb          # Advanced analysis notebook
├── powerbi/
│   └── dashboard.pbix             # Power BI dashboard file
├── tableau/
│   └── dashboard.twbx             # OR Tableau workbook (if using Tableau)
├── docs/
│   ├── executive_summary.pdf      # Executive summary document
│   └── data_dictionary.md         # Data dictionary
├── screenshots/
│   ├── dashboard_page1.png        # Dashboard screenshots
│   ├── dashboard_page2.png
│   └── dashboard_page3.png
└── presentation/
    └── final_presentation.pdf     # Optional presentation slides
README.md Must Include:
  • Your full name and submission date
  • Project title and executive summary (problem, approach, results)
  • Dataset description and source link
  • Tools used (Excel, SQL, Power BI/Tableau, Python)
  • Key findings (5-7 bullet points with metrics)
  • Business recommendations with supporting data
  • Limitations and future analysis opportunities
Do Include
  • All analysis files with clear outputs
  • Working Power BI/Tableau dashboard
  • Professional visualizations
  • Well-documented SQL queries
  • Executive summary with recommendations
  • Dashboard screenshots
Do Not Include
  • Very large raw data files (provide download link)
  • Temporary or cache files
  • Personal or sensitive information
  • Broken dashboard connections
  • Incomplete or draft work
  • Files without clear naming
05

Submission

Create a Google Drive folder with the exact name shown below and share with view access:

Required Folder Name
Data-Analytics-Final-Project-[YourName]
Example: Data-Analytics-Final-Project-JohnSmith
Important: Before submitting, make sure all files open correctly and the dashboard works without errors. Test the folder link in an incognito browser to verify access!
Submit Your Final Project

Enter your Google Drive folder link - we will verify your files automatically

06

Grading Rubric

Your final project will be graded on the following criteria:

Criteria Points Description
Data Handling and EDA 80 Data loading, cleaning, thorough exploratory analysis with meaningful visualizations
SQL Analysis 60 Well-written queries demonstrating various SQL techniques
Statistical Analysis 50 Appropriate statistical methods with correct interpretation
Dashboard Design 120 Professional Power BI/Tableau dashboard with interactivity and good UX
Business Insights 80 Actionable recommendations supported by data evidence
Documentation 60 Comprehensive README, executive summary, clear explanations
Presentation Quality 50 Professional formatting, consistent design, clear storytelling
Total 500
Bonus Points (Up to 50)
  • +15 pts: Python analysis with pandas and visualizations
  • +15 pts: Published to Power BI Service or Tableau Public
  • +10 pts: Exceptional visualizations (publication quality)
  • +10 pts: Video walkthrough of dashboard
Grading Scale
Excellent
450-500

90-100%

Good
400-449

80-89%

Satisfactory
350-399

70-79%

Needs Work
<350

<70%

Ready to Submit?

Make sure you have completed all requirements and reviewed the grading rubric above.

Submit Your Final Project
07

Pro Tips

Project Planning
  • Start with understanding your data first
  • Break the project into daily milestones
  • Document as you go, not at the end
  • Save versions of your dashboard regularly
Quality Over Quantity
  • Deep analysis beats more charts
  • Explain WHY each insight matters
  • Focus on actionable recommendations
  • Professional design matters
Time Management
  • Days 1-3: Data collection and EDA (25%)
  • Days 4-6: SQL and statistical analysis (25%)
  • Days 7-10: Dashboard creation (35%)
  • Days 11-12: Documentation and review (15%)
Common Pitfalls
  • Do not ignore data quality issues
  • Avoid cluttered dashboards
  • Do not make unsupported claims
  • Test your files before submitting
08

Pre-Submission Checklist

Technical Requirements
Documentation Requirements
Submission Requirements