Data Preparation and Processing
Data Processing Pipeline 🔄
Overview of Data Flow 📊
Data Extraction Methods 🔍
Automated Extraction Process
Method | DataType | Reliability |
---|---|---|
Excel Direct Read | Structured Tables | High |
Pattern Matching | Semi-structured | Medium |
Custom Parsers | Complex Formats | High |
Format Standardization 📋
Standardization Rules 📏
- Date Formats 📅
- ISO 8601 compliance
- Timezone handling
- Historical data conversion
- Numerical Values 🔢
- Decimal standardization
- Unit conversion
- Range validation
- Text Fields 📝
- Character encoding
- Case normalization
- Whitespace handling
Quality Control Checks ✅
Validation Framework
<- tibble::tribble(
validation_rules ~Rule, ~Description, ~Severity,
"Completeness", "Required fields present", "High",
"Format", "Data format compliance", "High",
"Range", "Values within bounds", "Medium",
"Consistency", "Cross-field validation", "High"
)
|>
validation_rules ::kable() knitr
Rule | Description | Severity |
---|---|---|
Completeness | Required fields present | High |
Format | Data format compliance | High |
Range | Values within bounds | Medium |
Consistency | Cross-field validation | High |