DE-7553: Smarten up the examples repo, organise things a bit (#19)

* DE-7553: Tidy up examples

* Add image

* Update README.md

Co-authored-by: Gunnar Morling <gunnar.morling@googlemail.com>

* Remove deprecated assets. Add note linking to PyFlink docs.

---------

Co-authored-by: Gunnar Morling <gunnar.morling@googlemail.com>

README.md

@@ -1,45 +1,85 @@
 # Decodable Examples
 
+![A squirrel holding a laptop that says "Examples repo"](images/examples_repo.webp)
+
+## Introduction
+
 This repository contains examples of use cases that utilize Decodable streaming solution as well as demos for related open-source projects such as Apache Flink, Debezium, and Postgres.
 
+Examples are presented "as-is" and are maintained on a best effort basis. PRs for updating existing (or adding new) examples are welcome!
+
+For help with any of the examples, or using Decodable in general, please [join our Slack group](https://join.slack.com/t/decodablecommunity/shared_invite/zt-uvow71bk-Uf914umgpoyIbOQSxriJkA).
+
+## About Decodable
+
+_Decodable radically simplifies real-time data, making it easier to access the freshest, high-quality data. Reduce infrastructure overhead, connect data sources, transform, and deliver data reliably to any destination._
+
+_Learn more [here](https://decodable.co), and [sign up for a free trial](https://app.decodable.co/-/accounts/create) today!_
+
 ## Contents
 
-| Example | Description |
-|---------|-------------|
-| [Flink Learn](./flink-learn/) | Apache Flink tutorials and webinar|
-| [AsyncAPI](asyncapi) | Publishing Data Products with AsyncAPI |
+### Stream Processing Techniques
+
+| Example                                     | Description                                                                                                    |
+|---------------------------------------------|----------------------------------------------------------------------------------------------------------------|
+| [Change Streams](change-streams)            | Using change streams to build materialized views in Postgres                                                   |
+| [XML Processing](xml)                       | Parse XML and transform to JSON                                                                                |
+| [Masking](masking)                          | Ways to mask data                                                                                              |
+| [Array Aggregation (1)](array-agg-postgres) | Demonstrating how to aggregate the elements of the many side of 1:n join into an array with data from Postgres |
+| [Array Aggregation (2)](array-agg)          | Using the `array_agg()` UDF for denormalizing data in a pipeline from MySQL to OpenSearch                      |
+
+### Data Pipelines
+
+| Example                                             | Description                                            |
+|-----------------------------------------------------|--------------------------------------------------------|
 | [Opinionated Data Pipelines](opinionated-pipelines) | Building data pipelines with schema on write streams. |
-| [Postman](postman) | Building data pipelines with Postman. |
-| [Change Streams](change-streams) | Using change streams to build materialized views in Postgres |
-| [XML Processing](xml) | Parse XML and transform to JSON |
-| [OSQuery Routing](osquery) | Route OSQuery logs with SQL |
-| [Masking](masking) | Ways to mask data |
-| [Apache Pinot](pinot) | Transforming osquery logs to Apache Pinot and Superset |
-| [Apache Druid](druid) | This example sends covid 19 data to Decodable using it's REST API. The data is then cleansed using Decodable SQL and send the data to a Kafka sink.  |
-| [Rockset](rockset) | We will be utilizing a cloud MQTT broker and AWS Kinesis to capture and stream data. Decodable will be responsible for preparing and aggregating the data prior to reaching the real-time analytical database (Rockset) |
-| [Tinybird](tinybird) | We write data to Tinybird and build a simple real time web application. |
-| [Apache Kafka](kafka2s3) | Installing Apache Kafka on EC2 and writing to S3 with Decodable |
-| [Apache Kafka mTLS](mtls) | We install Apache Kafka on EC2 and configure it with mTLS and configure Decodable to read from it |
-| [Snowflake + Snowpipe](snowflake) | We setup a snowpipe at the end of a Decodable S3 sink. |
-| [Confluent](confluent) | Clickstream from Confluent Cloud joined with CDC user data from Postgres |
-| [Snowflake + Snowpipe + Merge](snowflake/README-CDC.md) | Leveraging Snowpipe, we send CDC data from Postgres to be processed in Snowflake using an Append Only Stream in Snowflake to merge CDC data in a Snowflake table. Essentially `mirroring` the table in Postgres in a Snowflake table. |
-|[Reading S3 Events in a Lambda Function](s3events/)|We configure an S3 bucket with a Lambda notification to send data to Kinesis to be processed in Decodable |
-|[MSSQL CDC](mssql_cdc/)| We enable a MSSQL in Docker with CDC. We then stand up a Debezium server to read from MSSQL and write the change events into AWS Kinesis  |
-|[Oracle CDC](oracle_cdc/)| We configure a Oracle AWS RDS with LogMiner. We then stand up a Debezium server to read change events into AWS Kinesis  |
-|[DynamoDb CDC](dynamodb_cdc/)| We configure a DynamoDB to send change data to Kinesis. Then we read those changes into Decodable for transformation or replication.  |
-|[ Logical Decoding Message Examples](postgres-logical-decoding)| We show how to retrieve logical decoding messages from the Postgres WAL |
-|[GitHub Webhooks](github-webhooks)| We show how to process GitHub Webhook events using the Decodable REST source connector |
-|[PyFlink](pyflink)| We run a basic PyFlink job on Kubernetes |
-|[Kafka / Flink / Iceberg](kafka-iceberg/apache-flink)| Integrating Apache Kafka with Apache Iceberg through Apache Flink. _As presented at Kafka Summit London 2024_|
-|[Kafka / Flink / Iceberg](kafka-iceberg/decodable) (with Decodable)| Streaming from Apache Kafka to Apache Iceberg with Decodable|
-|[Flink SQL Troubleshooting](troubleshooting-flinksql)| A set of Docker Compose environments for demonstrating various Flink SQL troubleshooting scenarios (see [related blog](https://www.decodable.co/blog/flink-sql-misconfiguration-misunderstanding-and-mishaps?utm_medium=github&utm_source=examples_repo&utm_campaign=blog&utm_content=troubleshooting-flinksql))|
-|[Array Aggregation](array-agg)| Using the `array_agg()` UDF for denormalizing data in a pipeline from MySQL to OpenSearch |
-|[Kafka with ngrok](kafka-ngrok)| Docker Compose for running Apache Kafka locally, accessible from the internet using ngrok|
-|[PyFlink on Decodable](pyflink-decodable)| Running a PyFlink job as a Custom Pipeline on Decodable|
-|[Delta Lake / Flink](flink-delta-lake)| Writing to Delta Lake with Apache Flink |
+| [Postman](postman)                                  | Building data pipelines with Postman.                  |
 
+### PyFlink
 
-## License
+_Decodable provides a managed PyFlink service. Learn more [here](https://docs.decodable.co/pipelines/create-pipelines-using-your-own-apache-flink-jobs.html#_create_a_custom_pipeline_python)._
+
+| Example                                    | Description                                             |
+|--------------------------------------------|---------------------------------------------------------|
+| [PyFlink](pyflink)                         | Running a basic PyFlink job on Kubernetes               |
+| [PyFlink on Decodable](pyflink-decodable)  | Running a PyFlink job as a Custom Pipeline on Decodable |
+
+### Integrations
+
+| Example                                                                    | Description                                                                                                                                                                                                          |
+|----------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------|
+| [Apache Druid](druid)                                                      | Sending COVID-19 data to Decodable using its REST API, cleaning it with SQL, and then sending it to Apache Druid      |
+| [Apache Kafka / Flink / Iceberg](kafka-iceberg/apache-flink)               | Integrating Apache Kafka with Apache Iceberg through Apache Flink. _As presented at Kafka Summit London 2024_         |
+| [Apache Kafka / Flink / Iceberg](kafka-iceberg/decodable) (with Decodable) | Streaming from Apache Kafka to Apache Iceberg with Decodable                                                          |
+| [Apache Kafka Upsert connector](kafka-upsert/)                             | Explaining the difference between the Flink Kafka and Kafka Upsert connectors                                         |
+| [Apache Kafka mTLS](mtls)                                                  | Installing Apache Kafka on EC2 and configuring it with mTLS                                                           |
+| [Apache Kafka with ngrok](kafka-ngrok)                                     | Using Docker Compose for running Apache Kafka locally, accessible from the internet using ngrok                       |
+| [Apache Kafka](kafka2s3)                                                   | Installing Apache Kafka on EC2 and writing to S3 with Decodable                                                       |
+| [Apache Pinot](pinot)                                                      | Transforming osquery logs to Apache Pinot and Superset                                                                |
+| [AsyncAPI](asyncapi)                                                       | Publishing Data Products with AsyncAPI                                                                                |
+| [Confluent](confluent)                                                     | Clickstream from Confluent Cloud joined with CDC user data from Postgres                                              |
+| [Delta Lake / Flink](flink-delta-lake)                                     | Writing to Delta Lake with Apache Flink                                                                               |
+| [GitHub Webhooks](github-webhooks)                                         | Processing GitHub Webhook events using the Decodable REST source connector                                            |
+| [OSQuery Routing](osquery)                                                 | Routing OSQuery logs with SQL                                                                                         |
+| [Redpanda](redpanda)                                                       | Reading and writing data to Redpanda from Flink                                                                       |
+| [S3 Events in a Lambda Function](s3events/)                                | Configuring an S3 bucket with a Lambda notification to send data to Kinesis to be processed in Decodable              |
+| [Tinybird](tinybird)                                                       | Writing data to Tinybird from Decodable                                                                               |
+
+### Changed Data Capture (CDC)
 
-This code base is available under the Apache License, version 2.
+| Example                                                          | Description                                                                                                          |
+|------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------|
+| [MSSQL CDC](mssql_cdc/)                                          | Enabling MSSQL in Docker with CDC, reading from it with Debezium, writing change events into AWS Kinesis             |
+| [Oracle CDC](oracle_cdc/)                                        | Configuring Oracle AWS RDS with LogMiner, reading from it with Debezium, writing change events into AWS Kinesis      | 
+| [DynamoDb CDC](dynamodb_cdc/)                                    | Configure DynamoDB to send change data to Kinesis, reading changes into Decodable for transformation or replication. |
+| [ Logical Decoding Message Examples](postgres-logical-decoding)  | How to retrieve logical decoding messages from the Postgres WAL                                                      |
+
+### Flink SQL
+
+| Example                                               | Description |
+|-------------------------------------------------------|-------------|
+| [Flink SQL Troubleshooting](troubleshooting-flinksql) | A set of Docker Compose environments for demonstrating various Flink SQL troubleshooting scenarios (see [related blog](https://www.decodable.co/blog/flink-sql-misconfiguration-misunderstanding-and-mishaps?utm_medium=github&utm_source=examples_repo&utm_campaign=blog&utm_content=troubleshooting-flinksql))|
+
+## License
 
+This code base is available under the Apache License, version 2.

druid/README.md

@@ -1,6 +1,6 @@
 # COVID 19 Stats to Apache Druid and Imply Polaris
 
-This example sends covid 19 data to Decodable using it's REST API. The data is then cleansed using Decodable SQL - from there, data can be sent to Apache Druid (via Kafka) or an Imply Polaris table. You must have Kafka available if you want to stream to Druid. This example uses Confluent cloud as its Kafka. You must also have an Apache Druid running. Follow the install instructions for Druid [here](https://druid.apache.org/docs/latest/tutorials/index.html).
+This example sends COVID-19 data to Decodable using its REST API. The data is then cleansed using Decodable SQL - from there, data can be sent to Apache Druid (via Kafka) or an Imply Polaris table. You must have Kafka available if you want to stream to Druid. This example uses Confluent cloud as its Kafka. You must also have an Apache Druid running. Follow the install instructions for Druid [here](https://druid.apache.org/docs/latest/tutorials/index.html).
 
 ```mermaid
 flowchart TD;