diff --git a/finance-credit-card-chatbot/credit-card-analytics/creditcard-kafka/rewardsink.table.sql b/finance-credit-card-chatbot/credit-card-analytics/creditcard-kafka/rewardsink.table.sql
deleted file mode 100644
index 5bf9dba7..00000000
--- a/finance-credit-card-chatbot/credit-card-analytics/creditcard-kafka/rewardsink.table.sql
+++ /dev/null
@@ -1,13 +0,0 @@
-CREATE TABLE CustomerReward (
-     PRIMARY KEY (`customerId`) NOT ENFORCED
-) WITH (
-      'connector' = 'kafka',
-      'properties.bootstrap.servers' = '${PROPERTIES_BOOTSTRAP_SERVERS}',
-      'properties.group.id' = 'mygroupid',
-      'scan.startup.mode' = 'group-offsets',
-      'properties.auto.offset.reset' = 'earliest',
-      'key.format' = 'raw',
-      'key.fields' = 'customerId',
-      'value.format' = 'flexible-json',
-      'topic' = 'customerreward'
-      );
\ No newline at end of file
diff --git a/getting-started-examples/00_getting_started/README.md b/getting-started-examples/00_getting_started/README.md
deleted file mode 100644
index 8bdbf3e6..00000000
--- a/getting-started-examples/00_getting_started/README.md
+++ /dev/null
@@ -1,83 +0,0 @@
-# DataSQRL Personal Examples
-
-This repository contains a curated set of practical, beginner-friendly examples for learning and experimenting with [DataSQRL](https://github.com/DataSQRL/sqrl). Each example demonstrates a real-world data pipeline pattern using technologies like Kafka, Iceberg, Glue, and Schema Registry.
-
-## 📁 Example Index
-
-| Folder                                           | Description                                                                                            |
-| ------------------------------------------------ |--------------------------------------------------------------------------------------------------------|
-| **01\_kafka\_to\_console**                       | Reads from Kafka and outputs to console. Simple setup for basic Kafka ingestion testing.               |
-| **02\_kafka\_to\_kafka**                         | Reads from one Kafka topic and writes to another. Useful for learning basic Kafka transformations.     |
-| **03\_two\_streams\_kafka\_to\_kafka**           | Combines two Kafka topics, performs stream joins/enrichment, and writes to Kafka.                      |
-| **04\_two\_streams\_external\_kafka\_to\_kafka** | Simulates a more decoupled version of multi-stream joins. Good for external integration scenarios.     |
-| **05\_file\_iceberg\_test**                      | Writes data to local file-based Iceberg tables. Great for learning Iceberg without cloud dependencies. |
-| **06\_external\_kafka\_iceberg\_test**           | Kafka to Iceberg using a local warehouse directory. Minimal config, good for staging/testing.          |
-| **07\_external\_kafka\_iceberg\_glue\_test**     | Kafka to Iceberg using AWS Glue as catalog and S3 as storage.                                          |
-| **08\_schema\_registry\_kafka\_to\_kafka**       | Kafka-to-Kafka pipeline using Confluent Schema Registry for Avro schema management.                    |
-
-Each folder includes:
-
-* `package.json`: Configuration for engines, connectors, and environment
-* `.sqrl` script(s): The logic for the pipeline
-* `data_generator/`: Input data generation scripts and sample files
-
----
-
-## 🚀 Getting Started
-
-### Prerequisites
-
-* [Docker](https://docs.docker.com/get-docker/) installed
-* Optional: Kafka and Schema Registry (locally or in cloud)
-* For Glue/S3 integration: AWS CLI credentials (`~/.aws`) mounted in Docker
-
-### Run Any Example
-
-```bash
-docker run -it --rm \
-  -p 8888:8888 \
-  -p 8081:8081 \
-  -v $PWD:/build \
-  datasqrl/cmd:dev run -c package.json
-```
-
-If using AWS or external services, extend with environment mounts:
-
-```bash
-docker run -it --rm \
-  -p 8888:8888 \
-  -p 8081:8081 \
-  -v $PWD:/build \
-  -v ~/.aws:/root/.aws \
-  -e AWS_REGION=us-east-1 \
-  -e S3_WAREHOUSE_PATH=s3://your-bucket/path/ \
-  datasqrl/cmd:dev run -c package.json
-```
-
-### Compile Without Running
-
-```bash
-docker run -it --rm \
-  -v $PWD:/build \
-  datasqrl/cmd:dev compile -c package.json
-```
-
----
-
-## 🤔 Why These Examples?
-
-These examples are designed to:
-
-* Be self-contained and runnable out-of-the-box
-* Good to get started with datasqrl
-* Serve as a foundation for building your own DataSQRL pipelines
-
----
-
-## 📚 Learn More
-
-* 📘 [DataSQRL Docs](https://datasqrl.github.io/sqrl)
-* 💻 [GitHub Repository](https://github.com/DataSQRL/sqrl)
-* 💬 [Community Discord](https://docs.datasqrl.com/community/)
-
-Feel free to fork and build on top of these examples!
diff --git a/getting-started-examples/01_kafka_to_console/README.md b/getting-started-examples/01_kafka_to_console/README.md
index 67ddf4a2..aebdc757 100644
--- a/getting-started-examples/01_kafka_to_console/README.md
+++ b/getting-started-examples/01_kafka_to_console/README.md
@@ -3,21 +3,19 @@
 This project demonstrates how to use [DataSQRL](https://datasqrl.com) to build a streaming pipeline that:
 
 - Reads data from a kafka topic and prints output to console
-- Kafka is part of datasqrl package.
-
-
+- Kafka is part of the DataSQRL package.
 
 ## 🐳 Running DataSQRL
 
 Run the following command from the project root where your `package.json` and SQRL scripts reside:
 
 ```bash
-docker run -it --rm   -p 8888:8888 -p 9092:9092  -v $PWD:/build   datasqrl/cmd:dev run -c package.json
+docker run -it --rm -p 8888:8888 -p 9092:9092 -v $PWD:/build datasqrl/cmd:0.7.0 run -c package.json
 ```
 
 ## Generate Data
 
 * Go to `data-generator` folder 
 ```bash
- python3 send_kafka_avro_records.py ../kafka-source/contact.avsc data.jsonl contact localhost:9092
-```
\ No newline at end of file
+python3 send_kafka_avro_records.py ../kafka-source/contact.avsc data.jsonl contact localhost:9092
+```
diff --git a/getting-started-examples/01_kafka_to_console/kafka-console.sqrl b/getting-started-examples/01_kafka_to_console/kafka-console.sqrl
index 2659493c..2d1b05f6 100644
--- a/getting-started-examples/01_kafka_to_console/kafka-console.sqrl
+++ b/getting-started-examples/01_kafka_to_console/kafka-console.sqrl
@@ -1,4 +1,4 @@
 IMPORT kafka-source.Contact;
 
 -- Export the results to console (print)
-EXPORT Contact TO print.Contact;
\ No newline at end of file
+EXPORT Contact TO print.Contact;
diff --git a/getting-started-examples/01_kafka_to_console/package.json b/getting-started-examples/01_kafka_to_console/package.json
index aba2b763..7cd4067c 100644
--- a/getting-started-examples/01_kafka_to_console/package.json
+++ b/getting-started-examples/01_kafka_to_console/package.json
@@ -13,10 +13,5 @@
   },
   "test-runner": {
     "create-topics": ["contact", "contact"]
-  },
-  "dependencies": {
-    "metrics": {
-      "folder": "kafka-source"
-    }
   }
 }
diff --git a/getting-started-examples/02_kafka_to_kafka/README.md b/getting-started-examples/02_kafka_to_kafka/README.md
index 3f2c16bd..02b68dac 100644
--- a/getting-started-examples/02_kafka_to_kafka/README.md
+++ b/getting-started-examples/02_kafka_to_kafka/README.md
@@ -3,16 +3,14 @@
 This project demonstrates how to use [DataSQRL](https://datasqrl.com) to build a streaming pipeline that:
 
 - Reads data from a kafka topic and writes to another kafka topic
-- Kafka is part of datasqrl package.
-
-
+- Kafka is part of the DataSQRL package.
 
 ## 🐳 Running DataSQRL
 
 Run the following command from the project root where your `package.json` and SQRL scripts reside:
 
 ```bash
-docker run -it --rm   -p 8888:8888 -p 9092:9092  -v $PWD:/build   datasqrl/cmd:dev run -c package.json
+docker run -it --rm -p 8888:8888 -p 9092:9092  -v $PWD:/build datasqrl/cmd:0.7.0 run -c package.json
 ```
 
 ## Generate Data
@@ -25,4 +23,4 @@ docker run -it --rm   -p 8888:8888 -p 9092:9092  -v $PWD:/build   datasqrl/cmd:d
 
 ## Output
 
-* Updated records should be generated in contactupdated topic. 
\ No newline at end of file
+* Updated records should be generated in `contactupdated` topic. 
diff --git a/getting-started-examples/02_kafka_to_kafka/kafka-test.sqrl b/getting-started-examples/02_kafka_to_kafka/kafka-test.sqrl
index 99cf7588..11c30413 100644
--- a/getting-started-examples/02_kafka_to_kafka/kafka-test.sqrl
+++ b/getting-started-examples/02_kafka_to_kafka/kafka-test.sqrl
@@ -2,4 +2,4 @@ IMPORT kafka-source.Contact as Contacts;
 
 ContactsUpdated := SELECT firstname, lastname, last_updated FROM Contacts;
 
-EXPORT ContactsUpdated TO kafkasink.ContactUpdated;
\ No newline at end of file
+EXPORT ContactsUpdated TO kafka-sink.ContactUpdated;
diff --git a/getting-started-examples/02_kafka_to_kafka/package.json b/getting-started-examples/02_kafka_to_kafka/package.json
index cdbd1243..db4378ff 100644
--- a/getting-started-examples/02_kafka_to_kafka/package.json
+++ b/getting-started-examples/02_kafka_to_kafka/package.json
@@ -13,13 +13,5 @@
   },
   "test-runner": {
     "create-topics": ["contact", "contactupdated"]
-  },
-  "dependencies": {
-    "kafkasource": {
-      "folder": "kafka-source"
-    },
-    "kafkasink": {
-      "folder": "kafka-sink"
-    }
   }
 }
diff --git a/getting-started-examples/03_two_streams_kafka_to_kafka/README.md b/getting-started-examples/03_two_streams_kafka_to_kafka/README.md
index 73cec4b4..fcb8ebaa 100644
--- a/getting-started-examples/03_two_streams_kafka_to_kafka/README.md
+++ b/getting-started-examples/03_two_streams_kafka_to_kafka/README.md
@@ -13,7 +13,7 @@ This project demonstrates how to use [DataSQRL](https://datasqrl.com) to build a
 Run the following command from the project root where your `package.json` and SQRL scripts reside:
 
 ```bash
-docker run -it --rm   -p 8888:8888 -p 9092:9092  -v $PWD:/build   datasqrl/cmd:dev run -c package.json
+docker run -it --rm -p 8888:8888 -p 9092:9092 -v $PWD:/build datasqrl/cmd:0.7.0 run -c package.json
 ```
 
 ## Generate Data
@@ -32,4 +32,4 @@ docker run -it --rm   -p 8888:8888 -p 9092:9092  -v $PWD:/build   datasqrl/cmd:d
 
 ## Output
 
-* Updated records should be generated in enrichedcontact topic. 
\ No newline at end of file
+* Updated records should be generated in enrichedcontact topic. 
diff --git a/getting-started-examples/03_two_streams_kafka_to_kafka/kafka-test.sqrl b/getting-started-examples/03_two_streams_kafka_to_kafka/kafka-test.sqrl
index b8c0cfda..a705e1c6 100644
--- a/getting-started-examples/03_two_streams_kafka_to_kafka/kafka-test.sqrl
+++ b/getting-started-examples/03_two_streams_kafka_to_kafka/kafka-test.sqrl
@@ -7,4 +7,4 @@ EnrichedContacts := SELECT c.id, c.firstname, c.lastname, o.orgname, c.last_upda
                         ON c.id = o.userid
                         AND c.last_updated BETWEEN o.last_updated - INTERVAL '30' SECOND AND o.last_updated + INTERVAL '30' SECOND;
 
-EXPORT EnrichedContacts TO kafkasink.EnrichedContact;
+EXPORT EnrichedContacts TO kafka-sink.EnrichedContact;
diff --git a/getting-started-examples/03_two_streams_kafka_to_kafka/package.json b/getting-started-examples/03_two_streams_kafka_to_kafka/package.json
index fab85ff7..f57a1360 100644
--- a/getting-started-examples/03_two_streams_kafka_to_kafka/package.json
+++ b/getting-started-examples/03_two_streams_kafka_to_kafka/package.json
@@ -13,13 +13,5 @@
   },
   "test-runner": {
     "create-topics": ["contact", "organization", "enrichedcontact"]
-  },
-  "dependencies": {
-    "kafkasource": {
-      "folder": "kafka-source"
-    },
-    "kafkasink": {
-      "folder": "kafka-sink"
-    }
   }
 }
diff --git a/getting-started-examples/04_two_streams_external_kafka_to_kafka/README.md b/getting-started-examples/04_two_streams_external_kafka_to_kafka/README.md
index 5fc74d88..260a2b4a 100644
--- a/getting-started-examples/04_two_streams_external_kafka_to_kafka/README.md
+++ b/getting-started-examples/04_two_streams_external_kafka_to_kafka/README.md
@@ -5,23 +5,23 @@ This project demonstrates how to use [DataSQRL](https://datasqrl.com) to build a
 - This example uses kafka that is running outside of docker on host machine
 - Reads data from two kafka topics and combines the data from two streams using temporal join
 - Writes output to another kafka topic running on host machine
-- We are not using kafka running inside of datasqrl
+- We are not using kafka running inside DataSQRL
 
 ## Few things to note
 
-1. `'properties.bootstrap.servers' = 'host.docker.internal:9092'`, -> this tells docker to connect to your host machine's kafka
-2. You don't need to create output topic `enrichedcontact`
-3. `create-topics` array from package.json was removed since we are using external kafka where we expect source topics to be present
-4. We removed kafka engine from `enabled-engines` array in package.json
-
+* `'properties.bootstrap.servers' = 'host.docker.internal:9092'` -> this tells docker to connect to your host machine's kafka 
+* You don't need to create output topic `enrichedcontact`
+* `create-topics` array from `package.json` was removed since we are using external Kafka, where we expect source topics to be present 
+* We removed kafka engine from `enabled-engines` array in `package.json`
 
 ## 🐳 Running DataSQRL
 
 Run the following command from the project root where your `package.json` and SQRL scripts reside:
-Note: We removed `-p 9092:9092` as we are using our own kafka running locally on host machine now
 ```bash
-docker run -it --rm -p 8888:8888 -p 8081:8081 -v $PWD:/build datasqrl/cmd:dev run -c package.json
+docker run -it --rm -p 8888:8888 -p 8081:8081 -v $PWD:/build -v $PWD/data:/data datasqrl/cmd:0.7.0 run -c package.json
 ```
+> [!NOTE]
+> We removed `-p 9092:9092` as we are using our own kafka running locally on host machine now
 
 ## Generate Data
 
@@ -36,9 +36,6 @@ docker run -it --rm -p 8888:8888 -p 8081:8081 -v $PWD:/build datasqrl/cmd:dev ru
  python3 load_data.py organization.jsonl localhost:9092 organization
 ```
 
-
 ## Output
 
-* Updated records should be generated in enrichedcontact topic.
-
-
+* Updated records should be generated in `enrichedcontact` table.
diff --git a/getting-started-examples/04_two_streams_external_kafka_to_kafka/kafka-docker/docker-compose.yml b/getting-started-examples/04_two_streams_external_kafka_to_kafka/docker-compose.yml
similarity index 100%
rename from getting-started-examples/04_two_streams_external_kafka_to_kafka/kafka-docker/docker-compose.yml
rename to getting-started-examples/04_two_streams_external_kafka_to_kafka/docker-compose.yml
diff --git a/getting-started-examples/04_two_streams_external_kafka_to_kafka/kafka-test.sqrl b/getting-started-examples/04_two_streams_external_kafka_to_kafka/kafka-test.sqrl
index a7768884..94496fe1 100644
--- a/getting-started-examples/04_two_streams_external_kafka_to_kafka/kafka-test.sqrl
+++ b/getting-started-examples/04_two_streams_external_kafka_to_kafka/kafka-test.sqrl
@@ -1,16 +1,15 @@
-IMPORT kafkasource.Contact AS Contacts;
-IMPORT kafkasource.Organization AS Organizations;
+IMPORT kafka-source.Contact AS Contacts;
+IMPORT kafka-source.Organization AS Organizations;
 
 /*
   Joins Contacts and Organizations
   Matches rows where the contact's id equals the organization's userid
   But only if their last_updated timestamps are within ±5 seconds of each other
 */
-
 EnrichedContacts := SELECT c.id, c.firstname, c.lastname, o.orgname, c.last_updated
                         FROM Contacts c
                         JOIN Organizations o
                         ON c.id = o.userid
                         AND c.last_updated BETWEEN o.last_updated - INTERVAL '30' SECOND AND o.last_updated + INTERVAL '30' SECOND;
 
-EXPORT EnrichedContacts TO kafkasink.EnrichedContact;
+EXPORT EnrichedContacts TO kafka-sink.EnrichedContact;
diff --git a/getting-started-examples/04_two_streams_external_kafka_to_kafka/package.json b/getting-started-examples/04_two_streams_external_kafka_to_kafka/package.json
index 58bcc373..38e97cb4 100644
--- a/getting-started-examples/04_two_streams_external_kafka_to_kafka/package.json
+++ b/getting-started-examples/04_two_streams_external_kafka_to_kafka/package.json
@@ -10,13 +10,5 @@
         "table.exec.source.idle-timeout": "60 s"
       }
     }
-  },
-  "dependencies": {
-    "kafkasource": {
-      "folder": "kafka-source"
-    },
-    "kafkasink": {
-      "folder": "kafka-sink"
-    }
   }
 }
diff --git a/getting-started-examples/05_file_iceberg_test/README.md b/getting-started-examples/05_file_iceberg_test/README.md
index 547d287c..b9864636 100644
--- a/getting-started-examples/05_file_iceberg_test/README.md
+++ b/getting-started-examples/05_file_iceberg_test/README.md
@@ -9,20 +9,13 @@ This project demonstrates how to use [DataSQRL](https://datasqrl.com) to build a
 Run the following command from the project root where your `package.json` and SQRL scripts reside:
 
 ```bash
-docker run -it --rm \
-  -p 8888:8888 -p 8081:8081 \
-  -v $PWD:/build \
-  -e LOCAL_WAREHOUSE_DIR=warehouse \
-  datasqrl/cmd:dev run -c package.json
+docker run -it --rm -p 8888:8888 -p 8081:8081 -v $PWD:/build -v $PWD/data:/data datasqrl/cmd:0.7.0 run -c package.json
 ```
-Note: It will store iceberg files in `warehouse` directory
-
-
 
+> [!NOTE]
+> Iceberg files will be stored in the `warehouse` directory set by `package.json`
 
 ## Output
 
-* There should be iceberg files and folders generated in warehouse directory
-* Data for the output table will reside in ProcessedData (as defined in the sqrl script)
-
-
+* There should be iceberg files and folders generated in `$PWD/data/iceberg` directory 
+* Data for the output table will reside in `ProcessedData` (as defined in the sqrl script)
diff --git a/getting-started-examples/05_file_iceberg_test/file-to-iceberg.sqrl b/getting-started-examples/05_file_iceberg_test/file-to-iceberg.sqrl
index a6ee9d15..7dec237a 100644
--- a/getting-started-examples/05_file_iceberg_test/file-to-iceberg.sqrl
+++ b/getting-started-examples/05_file_iceberg_test/file-to-iceberg.sqrl
@@ -1,4 +1,3 @@
-IMPORT file-data.MyFile AS InputFile;
+IMPORT testdata.MyFile AS InputFile;
 
 ProcessedData := SELECT id, name, amount, event_time FROM InputFile;
-
diff --git a/getting-started-examples/05_file_iceberg_test/package.json b/getting-started-examples/05_file_iceberg_test/package.json
index d8372dd8..b95113b0 100644
--- a/getting-started-examples/05_file_iceberg_test/package.json
+++ b/getting-started-examples/05_file_iceberg_test/package.json
@@ -18,10 +18,5 @@
       "catalog-type": "hadoop",
       "catalog-name": "mycatalog"
     }
-  },
-  "dependencies": {
-    "file-data": {
-      "folder": "file-data"
-    }
   }
 }
diff --git a/getting-started-examples/05_file_iceberg_test/file-data/MyFile.table.sql b/getting-started-examples/05_file_iceberg_test/testdata/MyFile.table.sql
similarity index 100%
rename from getting-started-examples/05_file_iceberg_test/file-data/MyFile.table.sql
rename to getting-started-examples/05_file_iceberg_test/testdata/MyFile.table.sql
diff --git a/getting-started-examples/05_file_iceberg_test/file-data/myfile.jsonl b/getting-started-examples/05_file_iceberg_test/testdata/myfile.jsonl
similarity index 100%
rename from getting-started-examples/05_file_iceberg_test/file-data/myfile.jsonl
rename to getting-started-examples/05_file_iceberg_test/testdata/myfile.jsonl
diff --git a/getting-started-examples/06_external_kafka_iceberg_test/README.md b/getting-started-examples/06_external_kafka_iceberg_test/README.md
index 1d1239c1..bb75d02c 100644
--- a/getting-started-examples/06_external_kafka_iceberg_test/README.md
+++ b/getting-started-examples/06_external_kafka_iceberg_test/README.md
@@ -2,21 +2,17 @@
 
 This project demonstrates how to use [DataSQRL](https://datasqrl.com) to build a streaming pipeline that:
 
-- This example uses kafka that is running outside of datasqrl docker on host machine
+- This example uses Kafka that is running outside DataSQRL docker on host machine
 - Reads data from kafka topic and writes to an iceberg table locally
 
-
 ## 🐳 Running DataSQRL
 
 Run the following command from the project root where your `package.json` and SQRL scripts reside:
-Note: We removed `-p 9092:9092` as we are using our own kafka running locally on host machine now
 ```bash
-docker run -it --rm \
-  -p 8888:8888 -p 8081:8081 \
-  -v $PWD:/build \
-  -e LOCAL_WAREHOUSE_DIR=warehouse \
-  datasqrl/cmd:dev run -c package.json
+docker run -it --rm -p 8888:8888 -p 8081:8081 -v $PWD:/build -v $PWD/data:/data datasqrl/cmd:0.7.0 run -c package.json
 ```
+> [!NOTE]
+> We removed `-p 9092:9092` as we are using our own kafka running locally on host machine now
 
 ## Generate Data
 
@@ -27,10 +23,6 @@ docker run -it --rm \
 python3 load_data.py contacts.jsonl contact
 ```
 
-
-
 ## Output
 
-* Updated records should be generated in enrichedcontact topic.
-
-
+* Updated records should be generated in `enrichedcontact` topic.
diff --git a/getting-started-examples/06_external_kafka_iceberg_test/iceberg-sink/EnrichedContact.table.sql b/getting-started-examples/06_external_kafka_iceberg_test/iceberg-sink/EnrichedContact.table.sql
index 3e7afd98..e41ee852 100644
--- a/getting-started-examples/06_external_kafka_iceberg_test/iceberg-sink/EnrichedContact.table.sql
+++ b/getting-started-examples/06_external_kafka_iceberg_test/iceberg-sink/EnrichedContact.table.sql
@@ -4,6 +4,6 @@ CREATE TABLE EnrichedContact (
   'connector' = 'iceberg',
   'catalog-name' = 'mycatalog',
   'catalog-type' = 'hadoop',
-  'warehouse' = '${LOCAL_WAREHOUSE_DIR}',
+  'warehouse' = '/data/iceberg',
   'format-version' = '2'
 );
diff --git a/getting-started-examples/06_external_kafka_iceberg_test/kafka-to-iceberg.sqrl b/getting-started-examples/06_external_kafka_iceberg_test/kafka-to-iceberg.sqrl
index ada55d7c..c479d146 100644
--- a/getting-started-examples/06_external_kafka_iceberg_test/kafka-to-iceberg.sqrl
+++ b/getting-started-examples/06_external_kafka_iceberg_test/kafka-to-iceberg.sqrl
@@ -6,4 +6,3 @@ EnrichedContacts := SELECT
   lastname,
   last_updated
 FROM Contacts;
-
diff --git a/getting-started-examples/06_external_kafka_iceberg_test/load_data.py b/getting-started-examples/06_external_kafka_iceberg_test/load_data.py
deleted file mode 100644
index 1eef958e..00000000
--- a/getting-started-examples/06_external_kafka_iceberg_test/load_data.py
+++ /dev/null
@@ -1,20 +0,0 @@
-import json
-import sys
-from kafka import KafkaProducer
-
-def load_data(file_path, topic):
-    producer = KafkaProducer(
-        bootstrap_servers='localhost:9092',
-        value_serializer=lambda v: json.dumps(v).encode('utf-8')
-    )
-    with open(file_path, 'r') as f:
-        for line in f:
-            record = json.loads(line)
-            producer.send(topic, record)
-    producer.flush()
-
-if __name__ == "__main__":
-    if len(sys.argv) != 3:
-        print("Usage: python load_data.py <jsonl_file> <topic>")
-        sys.exit(1)
-    load_data(sys.argv[1], sys.argv[2])
diff --git a/getting-started-examples/06_external_kafka_iceberg_test/package.json b/getting-started-examples/06_external_kafka_iceberg_test/package.json
index c47114e9..40dd2d1c 100644
--- a/getting-started-examples/06_external_kafka_iceberg_test/package.json
+++ b/getting-started-examples/06_external_kafka_iceberg_test/package.json
@@ -18,13 +18,5 @@
       "catalog-type": "hadoop",
       "catalog-name": "mycatalog"
     }
-  },
-  "dependencies": {
-    "kafka-source": {
-      "folder": "kafka-source"
-    },
-    "iceberg-sink": {
-      "folder": "iceberg-sink"
-    }
   }
 }
diff --git a/getting-started-examples/07_external_kafka_iceberg_glue_test/README.md b/getting-started-examples/07_external_kafka_iceberg_glue_test/README.md
index 10b62ede..33057453 100644
--- a/getting-started-examples/07_external_kafka_iceberg_glue_test/README.md
+++ b/getting-started-examples/07_external_kafka_iceberg_glue_test/README.md
@@ -5,18 +5,13 @@ This project demonstrates how to use [DataSQRL](https://datasqrl.com) to build a
 - This example demonstrates how to use kafka and glue 
 - We read from kafka topic and write data to s3 in iceberg glue format
 
-## Note:
-- To run this program you would need access to aws s3 
-- you should have a credentials file in your ~/.aws directory
-
+> [!IMPORTANT]
+> To run this program you would need access to AWS S3
+> You should have a credentials file in your ~/.aws directory
 
 ## 🐳 Running DataSQRL
 
 Run the following command from the project root where your `package.json` and SQRL scripts reside:
-
-Note: 
-- We removed `-p 9092:9092` as we are using our own kafka running locally on host machine now
-- you also need to set `s3://[BUCKET]/path/to/folder/`
 ```bash
 docker run -it --rm \
   -p 8888:8888 \
@@ -24,24 +19,22 @@ docker run -it --rm \
   -v $PWD:/build \
   -v ~/.aws:/root/.aws \
   -e AWS_REGION=us-east-1 \
-  -e S3_WAREHOUSE_PATH=s3://[BUCKET]/path/to/folder/ \
-  datasqrl/cmd:dev run -c package.json
-
+  -e S3_WAREHOUSE_PATH=s3://<bucket>/path/to/warehouse/ \
+  datasqrl/cmd:0.7.0 run -c package.json
 ```
+> [!NOTE]
+> We removed `-p 9092:9092` as we are using our own Kafka running locally on host machine now
+> You also need to set `s3://<bucket>/path/to/warehouse/`
 
 ## Generate Data
 
 * Go to `data-generator` folder
-   * `python3 load_data.py <jsonl_file> <kafka_broker_address> <topic_name>`
+  * `python3 load_data.py <jsonl_file> <kafka_broker_address> <topic_name>`
 * To send Contact data
 ```bash
 python3 load_data.py contacts.jsonl contact
 ```
 
-
-
 ## Output
 
-* Updated records should be generated in enrichedcontact topic.
-
-
+* Updated records should be generated in `enrichedcontact` table.
diff --git a/getting-started-examples/07_external_kafka_iceberg_glue_test/kafka-to-iceberg.sqrl b/getting-started-examples/07_external_kafka_iceberg_glue_test/kafka-to-iceberg.sqrl
index a1ee781e..6a833d9a 100644
--- a/getting-started-examples/07_external_kafka_iceberg_glue_test/kafka-to-iceberg.sqrl
+++ b/getting-started-examples/07_external_kafka_iceberg_glue_test/kafka-to-iceberg.sqrl
@@ -6,4 +6,3 @@ enrichedcontacts := SELECT
   lastname,
   last_updated
 FROM contacts;
-
diff --git a/getting-started-examples/07_external_kafka_iceberg_glue_test/package.json b/getting-started-examples/07_external_kafka_iceberg_glue_test/package.json
index d80e9917..fef37ff0 100644
--- a/getting-started-examples/07_external_kafka_iceberg_glue_test/package.json
+++ b/getting-started-examples/07_external_kafka_iceberg_glue_test/package.json
@@ -22,10 +22,5 @@
       "catalog-database": "nsdatabase",
       "write.upsert.enabled": "true"
     }
-  },
-  "dependencies": {
-    "kafka-source": {
-      "folder": "kafka-source"
-    }
   }
 }
diff --git a/getting-started-examples/08_schema_registry_kafka_to_kafka/README.md b/getting-started-examples/08_schema_registry_kafka_to_kafka/README.md
index 7c833989..cfdbdcd0 100644
--- a/getting-started-examples/08_schema_registry_kafka_to_kafka/README.md
+++ b/getting-started-examples/08_schema_registry_kafka_to_kafka/README.md
@@ -30,25 +30,21 @@ Run the following command from the project root where your `package.json` and SQ
 docker run -it --rm \
   -p 8888:8888 \
   -v $PWD:/build \
-  datasqrl/cmd:dev run -c package.json
+  datasqrl/cmd:0.7.0 run -c package.json
 ```
 
 ## Generate Data
 * Go to `data-generator` folder
-
-Usage:
-
-    python send_kafka_avro_records.py <schema.avsc> <data.jsonl> <topic> <broker> <schema-registry-url>
-
-Example:
-
-     python send_kafka_avro_records.py contact.avsc data.jsonl contact localhost:9092 http://localhost:8081
+  * `python3 send_kafka_avro_records.py <schema.avsc> <data.jsonl> <topic> <broker> <schema-registry-url>`
+* Send Contact data
+```bash
+python3 send_kafka_avro_records.py contact.avsc data.jsonl contact localhost:9092 http://localhost:8081
+```
 
 What it does:
-
-- Reads newline-delimited JSON (.jsonl) file.
+- Reads newline-delimited JSON (`.jsonl`) file.
 - Publishes each record as a Kafka message.
 - For example, to load static test files to Kafka topics.
 
 ## Output
-* You should see output topic created called enrichedcontact_avro with data in it
\ No newline at end of file
+* You should see output topic created called `enrichedcontact_avro` with data in it
diff --git a/getting-started-examples/08_schema_registry_kafka_to_kafka/kafka-to-kafka.sqrl b/getting-started-examples/08_schema_registry_kafka_to_kafka/kafka-to-kafka.sqrl
index 51bb4bde..f5d1704f 100644
--- a/getting-started-examples/08_schema_registry_kafka_to_kafka/kafka-to-kafka.sqrl
+++ b/getting-started-examples/08_schema_registry_kafka_to_kafka/kafka-to-kafka.sqrl
@@ -1,4 +1,4 @@
-IMPORT kafkasource.Contact AS Contact;
+IMPORT kafka-source.Contact AS Contact;
 
 EnrichedContactAvro := SELECT
   firstname,
@@ -6,5 +6,4 @@ EnrichedContactAvro := SELECT
   CAST(last_updated AS STRING) AS last_updated_str
 FROM Contact;
 
-EXPORT EnrichedContactAvro TO kafkasink.EnrichedContactAvro;
-
+EXPORT EnrichedContactAvro TO kafka-sink.EnrichedContactAvro;
diff --git a/getting-started-examples/08_schema_registry_kafka_to_kafka/load_data.py b/getting-started-examples/08_schema_registry_kafka_to_kafka/load_data.py
deleted file mode 100644
index 1eef958e..00000000
--- a/getting-started-examples/08_schema_registry_kafka_to_kafka/load_data.py
+++ /dev/null
@@ -1,20 +0,0 @@
-import json
-import sys
-from kafka import KafkaProducer
-
-def load_data(file_path, topic):
-    producer = KafkaProducer(
-        bootstrap_servers='localhost:9092',
-        value_serializer=lambda v: json.dumps(v).encode('utf-8')
-    )
-    with open(file_path, 'r') as f:
-        for line in f:
-            record = json.loads(line)
-            producer.send(topic, record)
-    producer.flush()
-
-if __name__ == "__main__":
-    if len(sys.argv) != 3:
-        print("Usage: python load_data.py <jsonl_file> <topic>")
-        sys.exit(1)
-    load_data(sys.argv[1], sys.argv[2])
diff --git a/getting-started-examples/08_schema_registry_kafka_to_kafka/package.json b/getting-started-examples/08_schema_registry_kafka_to_kafka/package.json
index dc59ba8a..12e6a1dd 100644
--- a/getting-started-examples/08_schema_registry_kafka_to_kafka/package.json
+++ b/getting-started-examples/08_schema_registry_kafka_to_kafka/package.json
@@ -11,13 +11,5 @@
         "table.exec.source.idle-timeout": "60 s"
       }
     }
-  },
-  "dependencies": {
-    "kafkasource": {
-      "folder": "kafka-source"
-    },
-    "kafkasink": {
-      "folder": "kafka-sink"
-    }
   }
 }
diff --git a/getting-started-examples/README.md b/getting-started-examples/README.md
new file mode 100644
index 00000000..327b0560
--- /dev/null
+++ b/getting-started-examples/README.md
@@ -0,0 +1,98 @@
+# DataSQRL Personal Examples
+
+This repository contains a curated set of practical, beginner-friendly examples for learning and experimenting with [DataSQRL](https://github.com/DataSQRL/sqrl).
+Each example demonstrates a real-world data pipeline pattern using technologies like Kafka, Iceberg, Glue, and Schema Registry.
+
+## 📁 Example Index
+
+| Folder                                                                                       | Description                                                                                            |
+|----------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------|
+| [**01\_kafka\_to\_console**](./01_kafka_to_console)                                          | Reads from Kafka and outputs to console. Simple setup for basic Kafka ingestion testing.               |
+| [**02\_kafka\_to\_kafka**](./02_kafka_to_kafka)                                              | Reads from one Kafka topic and writes to another. Useful for learning basic Kafka transformations.     |
+| [**03\_two\_streams\_kafka\_to\_kafka**](./03_two_streams_kafka_to_kafka)                    | Combines two Kafka topics, performs stream joins/enrichment, and writes to Kafka.                      |
+| [**04\_two\_streams\_external\_kafka\_to\_kafka**](./04_two_streams_external_kafka_to_kafka) | Simulates a more decoupled version of multi-stream joins. Good for external integration scenarios.     |
+| [**05\_file\_iceberg\_test**](./05_file_iceberg_test)                                        | Writes data to local file-based Iceberg tables. Great for learning Iceberg without cloud dependencies. |
+| [**06\_external\_kafka\_iceberg\_test**](./06_external_kafka_iceberg_test)                   | Kafka to Iceberg using a local warehouse directory. Minimal config, good for staging/testing.          |
+| [**07\_external\_kafka\_iceberg\_glue\_test**](./07_external_kafka_iceberg_glue_test)        | Kafka to Iceberg using AWS Glue as catalog and S3 as storage.                                          |
+| [**08\_schema\_registry\_kafka\_to\_kafka**](./08_schema_registry_kafka_to_kafka)            | Kafka-to-Kafka pipeline using Confluent Schema Registry for Avro schema management.                    |
+
+Each folder includes:
+
+* `package.json`: Configuration for engines, connectors, and environment
+* `.sqrl` script(s): The logic for the pipeline
+* `data_generator/`: Input data generation scripts and sample files
+
+---
+
+## 🚀 Getting Started
+
+### Prerequisites
+
+* [Docker](https://docs.docker.com/get-docker/) installed
+* Optional: Kafka and Schema Registry (locally or in cloud)
+* For Glue/S3 integration: AWS CLI credentials (`~/.aws`) mounted in Docker
+
+### Run Any Example
+
+```bash
+docker run -it --rm \
+  -p 8888:8888 \
+  -p 8081:8081 \
+  -v $PWD:/build \
+  datasqrl/cmd:0.7.0 run -c package.json
+```
+#### Persistent Data
+
+To preserve the internally persisted data after the Docker container stopped running, extend with `/data` mount:
+
+```bash
+docker run -it --rm \
+  -p 8888:8888 \
+  -p 8081:8081 \
+  -v $PWD:/build \
+  -v $PWD/data:/data \
+  datasqrl/cmd:0.7.0 run -c package.json
+```
+
+#### Mount External Services
+
+If using AWS or external services, extend with environment mounts:
+
+```bash
+docker run -it --rm \
+  -p 8888:8888 \
+  -p 8081:8081 \
+  -v $PWD:/build \
+  -v ~/.aws:/root/.aws \
+  -e AWS_REGION=us-east-1 \
+  -e S3_WAREHOUSE_PATH=s3://your-bucket/path/ \
+  datasqrl/cmd:0.7.0 run -c package.json
+```
+
+### Compile Without Running
+
+```bash
+docker run -it --rm \
+  -v $PWD:/build \
+  datasqrl/cmd:0.7.0 compile -c package.json
+```
+
+---
+
+## 🤔 Why These Examples?
+
+These examples are designed to:
+
+* Be self-contained and runnable out-of-the-box
+* Good to get started with DataSQRL
+* Serve as a foundation for building your own DataSQRL pipelines
+
+---
+
+## 📚 Learn More
+
+* 📘 [DataSQRL Docs](https://datasqrl.github.io/sqrl)
+* 💻 [GitHub Repository](https://github.com/DataSQRL/sqrl)
+* 💬 [Community Discord](https://docs.datasqrl.com/community/)
+
+Feel free to fork and build on top of these examples!