Activity Schema

Abstract

1. Introduction

The Activity Schema data model is a standard designed for modern data warehouses. It is designed to make data modeling and analysis substantially simpler, faster, and more reliable than existing methodologies (e.g. a star schema)

The core approach is to separate modeling from querying. Models should be fully independent: asking new data questions should not require creating new models. Instead, queries can combine any number of existing models to build anything they need.

This is done by modeling all data in the warehouse as a single time series table.

2. Objective

Repository for the ActivitySchema spec and supporting materials

This project demonstrates how modern tools can be applied to a real-world Data Science problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• See the project README for exact requirements
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/ActivitySchema/ActivitySchema.git
cd ActivitySchema

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Turn the analysis into an interactive dashboard
• Automate data refresh with a scheduled job
• Add a predictive model on top of the analysis

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What is the source of the dataset and how was missing data handled?
2. Which exploratory analysis steps revealed the most useful insight?
3. Why were these particular charts chosen to present the data?
4. Which statistical or ML technique supports the conclusions?
5. How could the analysis be automated or refreshed with new data?

9. Source Code & License

This project is developed by ActivitySchema and published on GitHub under the Apache License 2.0. Please follow the license terms and credit the original author when you use or modify this code.