0.1.1 Setup Wiki

[tusharchou]

How to contribute to local-data-platform 0.1.2 release

[tusharchou]

https://readthedocs.org/projects/local-data-platform/builds/25858650/?

[tusharchou]

• [x] added tutorial files
• [ ] to do rebuild and understand what more changes are required

[tusharchou]

https://github.com/tusharchou/local-data-platform/wiki

[ArpitaDhir]

@tusharchou here is the example PRD for the MVP. Please create an issue to align and close the PRD.

Product Requirements Document

Objective

This outlines the requirements for Local Data Platform, a web-based solution aimed at helping businesses make data-driven decisions.

The platform will allow users to:

1. Search for User insights
2. Predict User Behaviour wrt Business
3. Upload Business data for analysis
4. Download User Insights as CSV files

Problem Statement

Businesses often struggle to make informed decisions due to a lack of actionable insights. Access to predictive analytics tailored to their specific datasets remains limited, expensive, or overly complex.

Who are we solving for?

• Small to Medium-Sized Enterprises (SMEs): Businesses with limited access to dedicated data science teams or tools.
• Decision-Makers: Business owners, managers, or analysts seeking clear, actionable insights from their data.

Reasons it may not work?

1. Users might hesitate to upload sensitive business data
2. Insights might be too complex or irrelevant for the target audience
3. Issues with data ingestion, prediction accuracy, or CSV export functionality
4. Low adoption due to insufficient marketing

Phases

MVP Mission

1. Allow users to Log in/Sign up
2. Users should have business insights dashboard
3. They can search insights
4. They can manage insights i.e add and delete
5. Allows users to upload data to LDP
6. Enables downloading of actionable insights in CSV format.

Success Metrics

Adoption Metrics

• Number of registered businesses [Aim: 10]
• Percentage of users actively uploading data [Aim: 75%]
• Cost to conversion [Aim: 2$]

Engagement Metrics

• Time spent on the platform [Aim: 2 hr]
• Number of insights searched per user per hour [Aim: 5+]
• Number of insights downloaded per user per hour [Aim: 5+]

Customer Satisfaction

• User retention rates [Aim: 50%]
• User Churn rates [Aim: 20%]
• NPS Feedback [70]

Phase	Task	Timeline	Owner	Deliverables
Planning	Finalize PRD	24 Nov 24	Tushar	Approved Doc
Design	Create the handoff ready website design	15 Dec 24	Arpita	High-fidelity designs
Frontend Dev	Build website on Framer	20 Dec 24	Arpita	Local Website
Backend Dev	API and package integration	20 Dec 24	Tushar	APIs and backend services
Integration	Combine frontend and backend	22 Dec 24	Tushar	Fully functional Staging Website
Testing	QA and bug fixing	23 Dec 24	Tushar	Bug-free release-ready product
Marketing	Social posts to engage till Launch	23 Dec 24	Arpita	Social Posts
Deployment	Launch MVP	01 Jan 25	Tushar	Live platform

Specifications

Product Design

• Key Actions
  • Authentication & Onboarding
  • Upload local data/ Ingest data
  • Search for insights
  • Download button for CSV exports.
  • Landing page with USP
  • Dashboard page
    • showcasing insights
    • data upload/download options
    • pinned data insights
  • Frontend: Framer
  • Responsive Design

Backend Requirements

• Framework: Python
• Key Actions:
  • Data ingestion APIs for parsing and validating uploaded files.
  • Prediction model powered by LDP
  • RESTful APIs for frontend-backend communication.
  • Export functionality to create CSV files for download.
• Database:

Testing

• Unit Testing: Validate frontend components and backend APIs.
• Integration Testing: Ensure seamless interaction between frontend and backend.
• User Acceptance Testing (UAT): Validate product functionality with beta users.