Update README.md

README.md

@@ -9,6 +9,12 @@ SpicyBytes is an innovative food and grocery management platform aimed at reduci
 ├───.github
 │   └───workflows
 ├───dags
+│   ├───allminogcs.py
+│   ├───collector.py
+│   ├───etl_exploitation_zone.py
+│   ├───etl_formatted_zone.py
+│   ├───expiry_notification.py
+│   └───synthetic.py
 ├───data
 │   └───raw
 ├───landing_zone
@@ -33,6 +39,32 @@ SpicyBytes is an innovative food and grocery management platform aimed at reduci
 │       ├───customer_purchase
 │       ├───sentiment_reviews
 │       └───supermarket_products
+├───formatted_zone
+│   ├───business_review_sentiment.py
+│   ├───customer_location.py
+│   ├───customer_purchase.py
+│   ├───customer_sales.py
+│   ├───customers.py
+│   ├───dynamic_pricing.py
+│   ├───establishments_catalonia.py
+│   ├───estimate_expiry_date.py
+│   ├───estimate_perishability.py
+│   ├───expiry_notification.py
+│   ├───individual_review_sentiment.py
+│   ├───location.py
+│   └───mealdrecomend.py
+├───exploitation_zone
+│   ├───dim_cust_location.py
+│   ├───dim_date.py
+│   ├───dim_product.py
+│   ├───dim_sp_location.py
+│   ├───fact_business_cust_purchase.py
+│   ├───fact_business_inventory.py
+│   ├───fact_business_review.py
+│   ├───fact_cust_inventory.py
+│   ├───fact_cust_purchase.py
+│   ├───fact_customer_review.py
+│   └───schema.txt
 └───readme_info
 ```
 
@@ -67,3 +99,24 @@ The `collector.py` DAG collects data on a monthly basis, while the `synthetic.py
 The proposed high level architecture is employed for the P1 delivery methodology.
 
 
+# SpicyBytes P2 Delivery : Formatted Zone and Exploitation Zone
+
+## DAGs
+
+We have created several DAGs to manage the workflows within the following zones:
+
+1. **Formatted Zone**
+   - Manages the tasks related to data formatting and standardization.
+   - Sends formatted files to Google Cloud Storage.
+2. **Exploitation Zone**
+   - Handles data exploitation, including analysis and transformation tasks.
+   - Sends data to BigQuery and connects to Google Looker for further analysis and visualization.
+3. **Landing Zone**
+   - Manages the initial data landing, ingestion, and raw data handling.
+
+## How to Use
+
+1. **Setting Up**: Ensure all dependencies are installed and the environment is configured properly.
+2. **Executing DAGs**: The DAGs can be executed via the Airflow scheduler. Ensure the Airflow server is running and the DAGs are enabled in the Airflow UI.
+3. **Monitoring**: Monitor the execution of the DAGs through the Airflow UI for any errors or required interventions.
+