update synthDataGen, provide fix for MSFT codeGen

docs/Spark/gems/machine-learning/ml-openai.md

@@ -26,8 +26,8 @@ tags:
 
 The OpenAI Gem allows the Prophecy user to interact with the OpenAI API using two different requests:
 
-1. Compute text embeddings ([link](/docs/Spark/gems/machine-learning/ml-openai.md#compute-text-embeddings)).
-2. Answer a question, where the user has the option to provide context ([link](/docs/Spark/gems/machine-learning/ml-openai.md#answer-a-question-with-a-given-context)).
+1. Compute text embeddings
+2. Answer a question, where the user has the option to provide context
 
 Follow along to learn how to interact with the OpenAI API using Prophecy's easy-to-use interface. For an example set of Pipelines that use these Gems to create a Generative AI Chatbot, see this [guide.](/docs/getting-started/genaichatbot.md)
 

docs/Spark/gems/source-target/advanced/synthetic-data-generator/synthetic-data-generator.md

@@ -15,7 +15,7 @@ Generate synthetic data with this special kind of Source Gem.
 
 Generating mock data is crucial when building data Pipelines to simulate real-world scenarios for testing, validating, and optimizing Pipeline performance before using actual production data. It helps ensure the Pipeline handles various data formats, structures, and edge cases effectively, minimizing potential issues in a live environment.
 
-A wide range of synthetic data can be created using any column name and an array of data types. For example, generate browser history to track fictitious devices and the details on when that device visits a particular website with a particular click count and frequency.
+A wide range of synthetic data can be created using any column name and an array of data types. For example, generate browser history data as shown below.
 
 ![img](../../../img/synth_0_datasample.png)
 
@@ -56,6 +56,9 @@ What type of data do you need to generate? Specify the data structure using Rand
 
 ![img](../../../img/synth_3_properties.png)
 
+Generate column using a sequence of integers (left). Generate another column by referencing an existing catalog table (right). Randomly select elements of the foreign key from that table.  
+![img](../../../img/synth_7_seq_or_foreign.png)
+
 ### Infer the Schema
 
 Changes to the columns in the Properties tab are incorporated by inferring the schema in the Schema tab.

docs/concepts/teamuser.md

@@ -23,3 +23,14 @@ Teams represent a group of users who work together.
 Teams, User, and Git [Settings](https://app.prophecy.io/metadata/settings) are accessed by clicking the `Settings` icon at the bottom left of the menu bar. The following image shows the page and the available functionality.
 
 ![Team Page](./img/team_page.png)
+
+## Team Metadata
+
+Manage the entities within a team by accessing the team's metadata page. Click **(1) Metadata**, **(2) Teams**, and select the **(3) team of interest**. Now you can see all the metadata for that team - including Info, which Projects, Pipelines, Jobs, etc are owned by that team. Also, team admins can manage **(4) Settings** for the team.
+![Team metadata](./img/team_metadata.png)
+
+**[Execution Metrics](/docs/Spark/execution/execution-metrics.md)** - collect metrics and data samples for each execution.
+
+**Code Generation** - enable multi-file code generation in the case of code payload size limitations.
+
+**Advanced** - update the artifactid, generative AI settings, etc for the team's projects.