diff --git a/0_Azure/2_AzureAnalytics/0_Fabric/demos/30_dynamic_pipeline_nbkparameters.md b/0_Azure/2_AzureAnalytics/0_Fabric/demos/30_DynamicPipeline_nbkparametersADF.md
similarity index 99%
rename from 0_Azure/2_AzureAnalytics/0_Fabric/demos/30_dynamic_pipeline_nbkparameters.md
rename to 0_Azure/2_AzureAnalytics/0_Fabric/demos/30_DynamicPipeline_nbkparametersADF.md
index 979a977d7..46318cee2 100644
--- a/0_Azure/2_AzureAnalytics/0_Fabric/demos/30_dynamic_pipeline_nbkparameters.md
+++ b/0_Azure/2_AzureAnalytics/0_Fabric/demos/30_DynamicPipeline_nbkparametersADF.md
@@ -5,7 +5,7 @@ Costa Rica
[](https://github.com/)
[brown9804](https://github.com/brown9804)
-Last updated: 2025-03-03
+Last updated: 2025-03-05
----------
diff --git a/0_Azure/2_AzureAnalytics/0_Fabric/demos/31_FabricActivatorRulePipeline/GeneratesRandomData.ipynb b/0_Azure/2_AzureAnalytics/0_Fabric/demos/31_FabricActivatorRulePipeline/GeneratesRandomData.ipynb
new file mode 100644
index 000000000..ef4d12893
--- /dev/null
+++ b/0_Azure/2_AzureAnalytics/0_Fabric/demos/31_FabricActivatorRulePipeline/GeneratesRandomData.ipynb
@@ -0,0 +1 @@
+{"cells":[{"cell_type":"code","source":["# Generates Dummy json file in Files/\n","\n","# Import necessary libraries\n","from pyspark.sql import SparkSession\n","from pyspark.sql.types import *\n","import random\n","from datetime import datetime, timedelta\n","\n","# Initialize Spark session (if not already initialized)\n","spark = SparkSession.builder.appName(\"GenerateRandomData\").getOrCreate()\n","\n","# Function to generate random data\n","def generate_random_data(num_entries):\n"," data = []\n"," for i in range(1, num_entries + 1):\n"," name = f\"User{i}\"\n"," entry = {\n"," \"id\": i,\n"," \"name\": name,\n"," \"age\": random.randint(18, 65),\n"," \"email\": f\"{name.lower()}@example.com\",\n"," \"created_at\": (datetime.now() - timedelta(days=random.randint(0, 365))).strftime(\"%Y-%m-%d %H:%M:%S\")\n"," }\n"," data.append(entry)\n"," return data\n","\n","# Generate 10 random entries\n","random_data = generate_random_data(10)\n","\n","# Define schema for the DataFrame\n","schema = StructType([\n"," StructField(\"id\", IntegerType(), True),\n"," StructField(\"name\", StringType(), True),\n"," StructField(\"age\", IntegerType(), True),\n"," StructField(\"email\", StringType(), True),\n"," StructField(\"created_at\", StringType(), True)\n","])\n","\n","# Create a DataFrame from the random data\n","df_random_data = spark.createDataFrame(random_data, schema=schema)\n","\n","# Write the DataFrame to the Lakehouse in the specified path\n","output_path = \"abfss://{WORKSPACE-NAME}@onelake.dfs.fabric.microsoft.com/raw_Bronze.Lakehouse/Files/random_data\" # Replace {WORKSPACE-NAME}\n","df_random_data.write.format(\"delta\").mode(\"overwrite\").save(output_path)\n","\n","print(f\"Random data has been saved to the Lakehouse at '{output_path}'.\")"],"outputs":[],"execution_count":null,"metadata":{"microsoft":{"language":"python","language_group":"synapse_pyspark"}},"id":"8d820f25-3c2e-45b3-8a08-af78f0d45e1d"}],"metadata":{"kernel_info":{"name":"synapse_pyspark"},"kernelspec":{"name":"synapse_pyspark","language":"Python","display_name":"Synapse PySpark"},"language_info":{"name":"python"},"microsoft":{"language":"python","language_group":"synapse_pyspark","ms_spell_check":{"ms_spell_check_language":"en"}},"nteract":{"version":"nteract-front-end@1.0.0"},"spark_compute":{"compute_id":"/trident/default","session_options":{"conf":{"spark.synapse.nbs.session.timeout":"1200000"}}},"dependencies":{}},"nbformat":4,"nbformat_minor":5}
\ No newline at end of file
diff --git a/0_Azure/2_AzureAnalytics/0_Fabric/demos/31_FabricActivatorRulePipeline/README.md b/0_Azure/2_AzureAnalytics/0_Fabric/demos/31_FabricActivatorRulePipeline/README.md
new file mode 100644
index 000000000..c3dc87546
--- /dev/null
+++ b/0_Azure/2_AzureAnalytics/0_Fabric/demos/31_FabricActivatorRulePipeline/README.md
@@ -0,0 +1,124 @@
+# Microsoft Fabric: Automating Pipeline Execution with Activator
+
+Costa Rica
+
+[](https://github.com/)
+[brown9804](https://github.com/brown9804)
+
+Last updated: 2025-03-05
+
+----------
+
+> This process shows how to set up Microsoft Fabric Activator to automate workflows by detecting file creation events in a storage system and triggering another pipeline to run.
+
+List of Content (Click to expand)
+
+ - [Set Up the First Pipeline](#set-up-the-first-pipeline)
+ - [Configure Activator to Detect the Event](#configure-activator-to-detect-the-event)
+ - [Set Up the Second Pipeline](#set-up-the-second-pipeline)
+ - [Define the Rule in Activator](#define-the-rule-in-activator)
+ - [Test the Entire Workflow](#test-the-entire-workflow)
+ - [Troubleshooting If Needed](#troubleshooting-if-needed)
+
+
+
+ - Choose the appropriate event type, such as `File Created`.
+
+
+
+
+
+ - Add a source:
+
+
+
+
+
+ https://github.com/user-attachments/assets/43a9654b-e8d0-44da-80b9-9f528483fa3b
+
+2. **Test Event Detection**:
+ - Save the event and test it by manually running the first pipeline to ensure Activator detects the file creation.
+ - Check the **Event Details** screen in Activator to confirm the event is logged.
+
+ https://github.com/user-attachments/assets/6b21194c-54b4-49de-9294-1bf78b1e5acd
+
+## Set Up the Second Pipeline
+
+1. **Create the Pipeline**:
+ - In Microsoft Fabric, create the second pipeline that performs the next set of tasks.
+ - Ensure it is configured to accept external triggers.
+2. **Publish the Pipeline**: Publish the second pipeline and ensure it is ready to be triggered.
+
+ https://github.com/user-attachments/assets/5b630579-a0ec-4d5b-b973-d9b4fdd8254c
+
+## Define the Rule in Activator
+
+1. **Setup the Activator**:
+
+ https://github.com/user-attachments/assets/7c88e080-d5aa-4920-acd6-94c2e4ae0568
+
+2. **Create a New Rule**:
+ - In `Activator`, create a rule that responds to the event you just configured.
+ - Set the condition to match the event details (e.g., file name, path, or metadata).
+3. **Set the Action**:
+ - Configure the rule to trigger the second pipeline.
+ - Specify the pipeline name and pass any required parameters.
+3. **Save and Activate**:
+ - Save the rule and activate it.
+ - Ensure the rule is enabled and ready to respond to the event.
+
+ https://github.com/user-attachments/assets/5f139eeb-bab0-4d43-9f22-bbe44503ed75
+
+## Test the Entire Workflow
+
+1. **Run the First Pipeline**: Execute the first pipeline and verify that the trigger file is created.
+2. **Monitor Activator**: Check the `Event Details` and `Rule Activation Details` in Activator to ensure the event is detected and the rule is activated.
+3. **Verify the Second Pipeline**: Confirm that the second pipeline is triggered and runs successfully.
+
+ https://github.com/user-attachments/assets/0a1dab70-2317-4636-b0be-aa0cb301b496
+
+
+## Troubleshooting (If Needed)
+- If the second pipeline does not trigger:
+ 1. Double-check the rule configuration in Activator.
+ 2. Review the logs in Activator for any errors or warnings.
+
+
+