Update links and deployment instructions

demos/betting-behavior-analysis.mdx

@@ -70,7 +70,19 @@ Once RisingWave is installed and deployed, run the three SQL queries below to se
 
 To keep this demo simple, a Python script is used to generate and insert data into the tables created above. 
 
-Navigate to the [user_betting_behavior](https://github.com/risingwavelabs/awesome-stream-processing) folder in the [awesome-stream-processing](https://github.com/risingwavelabs/awesome-stream-processing) and run the `data_generator.py` file. This Python script utilizes the `psycopg2` library to establish a connection with RisingWave so you can generate and insert synthetic data into the tables `user_profiles`, `betting_history`, and `positions`. 
+Clone the [awesome-stream-processing](https://github.com/risingwavelabs/awesome-stream-processing) repository.
+
+```bash
+git clone https://github.com/risingwavelabs/awesome-stream-processing.git
+```
+
+Navigate to the [user_betting_behavior](https://github.com/risingwavelabs/awesome-stream-processing/tree/main/02-simple-demos/sports_betting/user_betting_behavior) folder.
+
+```bash
+cd awesome-stream-processing/tree/main/02-simple-demos/sports_betting/user_betting_behavior
+```
+
+Run the `data_generator.py` file. This Python script utilizes the `psycopg2` library to establish a connection with RisingWave so you can generate and insert synthetic data into the tables `positions` and `market_data`. 
 
 If you are not running RisingWave locally or using default credentials, update the connection parameters accordingly:
 

demos/inventory-management-forecast.mdx

@@ -49,7 +49,19 @@ Once RisingWave is installed and deployed, run the two SQL queries below to set
 
 To keep this demo simple, a Python script is used to generate and insert data into the tables created above. 
 
-Navigate to the [warehouse_inventory_mgmt](https://github.com/risingwavelabs/awesome-stream-processing) folder in the [awesome-stream-processing](https://github.com/risingwavelabs/awesome-stream-processing) and run the `data_generator.py` file. This Python script utilizes the `psycopg2` library to establish a connection with RisingWave so you can generate and insert synthetic data into the tables `inventory` and `sales`. 
+Clone the [awesome-stream-processing](https://github.com/risingwavelabs/awesome-stream-processing) repository.
+
+```bash
+git clone https://github.com/risingwavelabs/awesome-stream-processing.git
+```
+
+Navigate to the [warehouse_inventory_mgmt](https://github.com/risingwavelabs/awesome-stream-processing/tree/main/02-simple-demos/logistics/warehouse_inventory_mgmt) folder.
+
+```bash
+cd awesome-stream-processing/tree/main/02-simple-demos/logistics/warehouse_inventory_mgmt
+```
+
+Run the `data_generator.py` file. This Python script utilizes the `psycopg2` library to establish a connection with RisingWave so you can generate and insert synthetic data into the tables `positions` and `market_data`. 
 
 If you are not running RisingWave locally or using default credentials, update the connection parameters accordingly:
 

demos/market-data-enrichment.mdx

@@ -50,7 +50,19 @@ Once RisingWave is installed and deployed, run the two SQL queries below to set
 
 To keep this demo simple, a Python script is used to generate and insert data into the tables created above. 
 
-Navigate to the [market_data_enrichment](https://github.com/risingwavelabs/awesome-stream-processing) folder in the [awesome-stream-processing](https://github.com/risingwavelabs/awesome-stream-processing) and run the `data_generator.py` file. This Python script utilizes the `psycopg2` library to establish a connection with RisingWave so you can generate and insert synthetic data into the tables `raw_market_data` and `enrichment_data`. 
+Clone the [awesome-stream-processing](https://github.com/risingwavelabs/awesome-stream-processing) repository.
+
+```bash
+git clone https://github.com/risingwavelabs/awesome-stream-processing.git
+```
+
+Navigate to the [market_data_enrichment](https://github.com/risingwavelabs/awesome-stream-processing/tree/main/02-simple-demos/capital_markets/market_data_enrichment) folder.
+
+```bash
+cd awesome-stream-processing/tree/main/02-simple-demos/capital_markets/market_data_enrichment
+```
+
+Run the `data_generator.py` file. This Python script utilizes the `psycopg2` library to establish a connection with RisingWave so you can generate and insert synthetic data into the tables `positions` and `market_data`. 
 
 If you are not running RisingWave locally or using default credentials, update the connection parameters accordingly:
 

demos/market-trade-surveillance.mdx

@@ -52,7 +52,19 @@ Once RisingWave is installed and deployed, run the two SQL queries below to set
 
 To keep this demo simple, a Python script is used to generate and insert data into the tables created above. 
 
-Navigate to the [market_surveillance](https://github.com/risingwavelabs/awesome-stream-processing) folder in the [awesome-stream-processing](https://github.com/risingwavelabs/awesome-stream-processing) and run the `data_generator.py` file. This Python script utilizes the `psycopg2` library to establish a connection with RisingWave so you can generate and insert synthetic data into the tables `trade_data` and `market_data`. 
+Clone the [awesome-stream-processing](https://github.com/risingwavelabs/awesome-stream-processing) repository.
+
+```bash
+git clone https://github.com/risingwavelabs/awesome-stream-processing.git
+```
+
+Navigate to the [market_surveillance](https://github.com/risingwavelabs/awesome-stream-processing/tree/main/02-simple-demos/capital_markets/market_surveillance) folder.
+
+```bash
+cd awesome-stream-processing/tree/main/02-simple-demos/capital_markets/market_surveillance
+```
+
+Run the `data_generator.py` file. This Python script utilizes the `psycopg2` library to establish a connection with RisingWave so you can generate and insert synthetic data into the tables `positions` and `market_data`. 
 
 If you are not running RisingWave locally or using default credentials, update the connection parameters accordingly:
 

demos/sports-risk-profit-analysis.mdx

@@ -55,7 +55,19 @@ Once RisingWave is installed and deployed, run the two SQL queries below to set
 
 To keep this demo simple, a Python script is used to generate and insert data into the tables created above. 
 
-Navigate to the [position_risk_management](https://github.com/risingwavelabs/awesome-stream-processing) folder in the [awesome-stream-processing](https://github.com/risingwavelabs/awesome-stream-processing) and run the `data_generator.py` file. This Python script utilizes the `psycopg2` library to establish a connection with RisingWave so you can generate and insert synthetic data into the tables `positions` and `market_data`. 
+Clone the [awesome-stream-processing](https://github.com/risingwavelabs/awesome-stream-processing) repository.
+
+```bash
+git clone https://github.com/risingwavelabs/awesome-stream-processing.git
+```
+
+Navigate to the [position_risk_management](https://github.com/risingwavelabs/awesome-stream-processing/tree/main/02-simple-demos/sports_betting/position_risk_management) folder.
+
+```bash
+cd awesome-stream-processing/02-simple-demos/sports_betting/position_risk_management
+```
+
+Run the `data_generator.py` file. This Python script utilizes the `psycopg2` library to establish a connection with RisingWave so you can generate and insert synthetic data into the tables `positions` and `market_data`. 
 
 If you are not running RisingWave locally or using default credentials, update the connection parameters accordingly: