CWICR Data Validator

CWICR Data Validator

Business Case

Problem Statement

Data quality issues cause:

• Incorrect estimates
• Budget overruns
• Delayed projects
• Rework costs

Solution

Systematic validation of CWICR data and estimate inputs to catch errors, outliers, and inconsistencies before they impact projects.

Business Value

• Error prevention - Catch issues early
• Data quality - Ensure reliable estimates
• Consistency - Standard validation rules
• Audit trail - Document data issues

Technical Implementation

import pandas as pd
import numpy as np
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass, field
from enum import Enum
from datetime import datetime


class ValidationSeverity(Enum):
    """Validation issue severity."""
    ERROR = "error"          # Must fix
    WARNING = "warning"      # Should review
    INFO = "info"            # For awareness


class ValidationCategory(Enum):
    """Validation categories."""