Add Lab 11 data flow diagram

LAB_11_DIAGRAM.md

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+# Lab 11 Data Flow Diagram
+
+Open this file in Markdown Preview to render the Mermaid diagram.
+
+```mermaid
+%%{init: {'theme': 'neutral', 'flowchart': {'curve': 'linear', 'nodeSpacing': 35, 'rankSpacing': 55}}}%%
+flowchart TD
+    A["MTA operations generate daily ridership and traffic estimates"]:::source
+    B["NYC health reporting systems generate daily COVID case counts"]:::source
+
+    C["Open NY API<br/>Dataset: vxuj-8kew"]:::api
+    D["NYC Open Data API<br/>Dataset: rc75-m7u3"]:::api
+
+    E["Python batch loader<br/>load_data_to_bq.py"]:::loader
+    F["Cleaning and type conversion<br/>pandas parsing + column renaming"]:::loader
+    G["BigQuery tables<br/>mta_data.daily_ridership<br/>mta_data.nyc_covid_cases"]:::storage
+    H["Shared query utilities<br/>utils.py"]:::app
+    I["Streamlit pages<br/>dashboard + analysis views"]:::app
+    J["User-facing output<br/>charts, KPIs, and recovery analysis"]:::output
+
+    R1["Risk: upstream definitions or collection methods change"]:::risk
+    R2["Risk: API outage, timeout, or schema drift"]:::risk
+    R3["Risk: authentication failure or bad full refresh"]:::risk
+    R4["Risk: permissions, cache, or query errors"]:::risk
+
+    A --> C
+    B --> D
+    C --> E
+    D --> E
+    E --> F --> G --> H --> I --> J
+
+    A -.-> R1
+    B -.-> R1
+    C -.-> R2
+    D -.-> R2
+    E -.-> R3
+    G -.-> R4
+    H -.-> R4
+    I -.-> R4
+
+    classDef source fill:#d2e3fc,stroke:#5b9cf6,color:#202124,stroke-width:2px;
+    classDef api fill:#e4d7ff,stroke:#8b5cf6,color:#202124,stroke-width:2px;
+    classDef loader fill:#fde7c3,stroke:#f59e0b,color:#202124,stroke-width:2px;
+    classDef storage fill:#fbd3d0,stroke:#e56b5d,color:#202124,stroke-width:2px;
+    classDef app fill:#d7f1ea,stroke:#2ea76d,color:#202124,stroke-width:2px;
+    classDef output fill:#dbeafe,stroke:#3b82f6,color:#202124,stroke-width:2px;
+    classDef risk fill:#fff4cc,stroke:#d97706,color:#7c2d12,stroke-width:2px;
+```
+
+## What Happens
+
+- Two upstream organizations generate the source data.
+- The project pulls both datasets from public JSON APIs.
+- `load_data_to_bq.py` cleans the data and fully refreshes two BigQuery tables.
+- `utils.py` queries BigQuery and prepares data for the app.
+- Streamlit renders charts and analysis for the user.
+
+## What Can Go Wrong
+
+- Source definitions or field names may change upstream.
+- Public APIs may fail, timeout, or return unexpected schemas.
+- A failed batch load can overwrite a previously good table.
+- BigQuery permissions, caching, or app queries may fail.
+
+If Mermaid Preview is unavailable, use [LAB_11_DIAGRAM.svg](./LAB_11_DIAGRAM.svg) as the screenshot version.