📄️ Introduction
DataLoaf is an open-source, self-hostable product analytics platform. It aims to be easy to deploy and simple to implement in a new or existing code base. DataLoaf's target users are small to medium-sized companies that want to add data-informed decision making to their product.
📄️ Product Analytics
Product analytics is a branch of data analytics that focuses on gathering information about how users engage with a product. Companies can use that information to make data-informed decisions about how a product should evolve.
📄️ Architecture Overview
DataLoaf can be mentally divided into three sections, shown in the figure above. They are: data collection, data storage and data visualization.
📄️ Design Decisions and Tradeoffs
This section covers the five most impactful design decisions in DataLoaf’s creation. Each discussion covers the problems that needed to be solved, the solution that was chosen and why it was chosen over alternatives.
📄️ Conclusion
DataLoaf offers a self-hosted solution for integrating product analytics into small and medium-sized companies. It automates deployment via a CLI tool and provides an easy to use SDK for event and user data generation. Its infrastructure is designed to facilitate near real-time event streaming, and it provides a full stack application to interface with the captured data. Most importantly, its self-hosted nature grants full control over data and infrastructure, addressing the limitations of managed solutions.
📄️ References and Helpful Resources
[1] https://www.britannica.com/topic/Twitch-service (Twitch history)