Update smma/grant_starting.md

smma/grant_starting.md

@@ -291,4 +291,98 @@ Based purely on **ease of initial implementation for someone with zero experienc
 4.  **High Demand:** The non-profit and research sectors are constantly seeking grants, and many lack the internal resources or tech-savvy staff to efficiently search.
 5.  **Confidence Building:** Getting a working script to extract, filter, and output a clean CSV from Grants.gov will be a massive confidence booster for you. It proves your core skills translate into a valuable deliverable.
 
-**Immediate next step recommendation: Focus exclusively on downloading the Grants.gov Data Extract ZIP and successfully running the DuckDB script to filter it into a CSV.** Don't worry about selling until you've done that. That success will be your first step in building confidence.
+**Immediate next step recommendation: Focus exclusively on downloading the Grants.gov Data Extract ZIP and successfully running the DuckDB script to filter it into a CSV.** Don't worry about selling until you've done that. That success will be your first step in building confidence.
+
+---
+
+**Raw Data Ingestion Layer:**
+
+```python
+# Base ingestion interface
+class RawDataIngester:
+    def fetch_data(self, date_range=None):
+        """Download raw data from source"""
+        pass
+    
+    def validate_data(self, raw_data):
+        """Check file integrity, format"""
+        pass
+    
+    def store_raw(self, raw_data, metadata):
+        """Store exactly as received with metadata"""
+        pass
+
+# Source-specific implementations
+class GrantsGovIngester(RawDataIngester):
+    def fetch_data(self, date_range=None):
+        # Download XML extract ZIP
+        # Return file paths + metadata
+        pass
+
+class USASpendingIngester(RawDataIngester):
+    def fetch_data(self, date_range=None):
+        # Download CSV files (Full/Delta)
+        # Handle multiple file types
+        pass
+
+class SAMGovIngester(RawDataIngester):
+    def fetch_data(self, date_range=None):
+        # API calls or file downloads
+        pass
+```
+
+**Raw Storage Schema:**
+
+```sql
+-- Metadata tracking
+raw_data_batches (
+    id, source, batch_type, file_path, file_size, 
+    download_timestamp, validation_status, processing_status
+)
+
+-- Actual raw data (JSONB for flexibility)
+raw_data_records (
+    id, batch_id, source, record_type, 
+    raw_content JSONB, created_at
+)
+```
+
+**File Management:**
+- Store raw files in object storage (S3/MinIO)
+- Database only stores metadata + file references
+- Keep raw files for reprocessing/debugging
+
+**Ingestion Orchestrator:**
+
+```python
+class IngestionOrchestrator:
+    def run_ingestion_cycle(self):
+        for source in self.active_sources:
+            try:
+                # Fetch, validate, store
+                # Track success/failure
+                # Trigger downstream processing
+            except Exception:
+                # Alert, retry logic
+                pass
+```
+
+**Key Features:**
+- **Idempotent**: Can re-run safely
+- **Resumable**: Track what's been processed
+- **Auditable**: Full lineage from raw → processed
+- **Flexible**: Easy to add new data sources
+
+**Configuration Driven:**
+```yaml
+sources:
+  grants_gov:
+    enabled: true
+    schedule: "weekly"
+    url_pattern: "https://..."
+  usa_spending:
+    enabled: true
+    schedule: "monthly"
+```
+
+This layer just moves bytes around. Zero business logic. Want me to detail the validation layer next?