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Enterprise Reporting

Waterfall

Enterprise sales reporting & analytics platform

01

Overview

An internal enterprise platform that automates sales reporting and waterfall analytics. I worked on the Django backend and the Angular frontend: the business logic, the data-processing workflows, the reporting cycles, and the access model that scopes what each user can see.

02

Problem / Context

  • Sales reporting arrived as spreadsheets and had to become trustworthy, queryable reporting output — which makes upload handling, validation and exception handling the core of the problem, not incidental plumbing.
  • Reporting runs on fixed business cycles: weekly, monthly, quarterly and quarter-to-date. Each cycle has its own expectations of the same underlying data.
  • Users should only see the data belonging to them and their region, so access control had to be enforced in the data layer rather than hidden in the UI.

03

My Contribution

Backend & business logic

  • Django backend development
  • Core business logic
  • Database-driven workflows

Reporting & analytics

  • Sales reporting
  • Waterfall analytics
  • ROL processing
  • Weekly, monthly, quarterly and QTD reporting workflows

Data workflows

  • Excel/file upload workflows
  • Data validation and exception handling
  • Filtering, pagination and download functionality

Access control

  • User-based access control
  • Region-based access control

Frontend & stabilization

  • Angular frontend development
  • Dashboard functionality
  • Bug fixing and stabilization

04

Technologies

  • Django
  • Python
  • Angular
  • TypeScript
  • SQL

05

Key Engineering Areas

  • Django
  • Business logic
  • ROL processing
  • Excel upload workflows
  • Data validation
  • Exception handling
  • Access control
  • Region-based permissions
  • Reporting workflows
  • Data processing
  • Dashboard functionality

06

AI Extension

AI arrived on Waterfall later, as a separate workstream layered onto an already-working platform. The reporting engine itself is conventional Django and Angular engineering — the AI work below is an addition to it, not the substance of it.

  • MCP
  • LangChain
  • AI-powered chatbot / agent workflow implemented into the application

07

Outcome

  • Sales reporting is automated end to end across weekly, monthly, quarterly and QTD cycles, with upload, validation, filtering, pagination and download handled inside the platform.
  • Access is scoped per user and per region, so the same reporting surface serves different audiences without exposing data across boundaries.