budget service - #118

closes #111

PR Summary

Implement the budgets and analytics modules with real database-backed functionality, replacing the existing status-only scaffolds.
This PR adds full budget CRUD with ownership validation, introduces a new budgets table and entity, implements real transaction-based analytics queries, and consolidates the duplicate analytics modules into a single analytics module.

Changes

Budgets

• Added budgets database migration.

• Added Budget entity with:

  • id
  • userId
  • name
  • asset
  • amount
  • category
  • period
  • startDate
  • endDate
  • createdAt
  • updatedAt

• Replaced BudgetsService.status() with full CRUD:

  • Create budget
  • List user budgets
  • Get a specific budget
  • Update budget
  • Delete budget

• Added ownership checks to prevent users from accessing or modifying another user's budgets.

• Protected budget routes with JwtAuthGuard.

Analytics

Replaced the analytics status scaffold with real PostgreSQL queries against the existing transactions table.

Implemented:

• Spending Trend

  • Groups transactions by ISO week using date_trunc.
  • Supports configurable asset and week range.
  • Returns weekly spending totals.

• Category Breakdown

  • Aggregates spending by category.
  • Calculates category percentages against the grand total directly in SQL.
  • Supports asset and start-date filtering.

• Budget vs Actual

  • Joins budgets with transactions using category and asset.
  • Calculates budgeted amount, actual spending, and variance for each budget.

Analytics Consolidation

• Removed the duplicate src/analytics-system/ module.
• Moved any required unique functionality into src/analytics/.
• Removed AnalyticsSystemModule from app.module.ts.
• Updated the analytics module and controller to expose the implemented endpoints.
• Protected analytics routes with JwtAuthGuard.

Testing

Added unit tests covering:

• Budget creation and CRUD operations.
• Budget ownership validation.
• Budget update and deletion.
• Spending trend aggregation.
• Category breakdown and percentage calculations.
• Budget-vs-actual calculations.
• Analytics query behavior.