Modified readme and doc site pages

README.md

@@ -48,7 +48,7 @@ In practice, a single generic DLT pipeline reads the Dataflowspec and uses it to
 
 #### Metadata Interface
 
-- Capture input/output metadata in [onboarding file](https://github.com/databrickslabs/dlt-meta/blob/main/examples/onboarding.json)
+- Capture input/output metadata in [onboarding file](https://github.com/databrickslabs/dlt-meta/blob/main/examples/onboarding.template)
 - Capture [Data Quality Rules](https://github.com/databrickslabs/dlt-meta/tree/main/examples/dqe/customers/bronze_data_quality_expectations.json)
 - Capture processing logic as sql in [Silver transformation file](https://github.com/databrickslabs/dlt-meta/blob/main/examples/silver_transformations.json)
 

docs/content/_index.md

@@ -14,7 +14,7 @@ In practice, a single generic DLT pipeline reads the Dataflowspec and uses it to
 ### DLT-META components:
 
 #### Metadata Interface 
-- Capture input/output metadata in [onboarding file](https://github.com/databrickslabs/dlt-meta/blob/main/examples/onboarding.json)
+- Capture input/output metadata in [onboarding file](https://github.com/databrickslabs/dlt-meta/blob/main/examples/onboarding.template)
 - Capture [Data Quality Rules](https://github.com/databrickslabs/dlt-meta/tree/main/examples/dqe/customers/bronze_data_quality_expectations.json)
 - Capture  processing logic as sql in [Silver transformation file](https://github.com/databrickslabs/dlt-meta/blob/main/examples/silver_transformations.json)
 

docs/content/demo/Append_FLOW_CF.md

@@ -15,6 +15,11 @@ This demo will perform following tasks:
 1. Launch Terminal/Command prompt 
 
 2. Install [Databricks CLI](https://docs.databricks.com/dev-tools/cli/index.html)
+    - Once you install Databricks CLI, authenticate your current machine to a Databricks Workspace:
+
+    ```commandline
+    databricks auth login --host WORKSPACE_HOST
+    ```
 
 3. ```commandline
     git clone https://github.com/databrickslabs/dlt-meta.git 

docs/content/demo/Append_FLOW_EH.md

@@ -12,6 +12,11 @@ draft: false
 1. Launch Terminal/Command prompt 
 
 2. Install [Databricks CLI](https://docs.databricks.com/dev-tools/cli/index.html)
+    - Once you install Databricks CLI, authenticate your current machine to a Databricks Workspace:
+
+    ```commandline
+    databricks auth login --host WORKSPACE_HOST
+    ```
 
 3. ```commandline
     git clone https://github.com/databrickslabs/dlt-meta.git 

docs/content/demo/DAIS.md

@@ -17,14 +17,26 @@ This demo showcases DLT-META's capabilities of creating Bronze and Silver DLT pi
 1. Launch Terminal/Command promt 
 
 2. Install [Databricks CLI](https://docs.databricks.com/dev-tools/cli/index.html)
+    - Once you install Databricks CLI, authenticate your current machine to a Databricks Workspace:
+
+    ```commandline
+    databricks auth login --host WORKSPACE_HOST
+    ```
 
-3. ```git clone https://github.com/databrickslabs/dlt-meta.git ```
+3. ```commandline
+    git clone https://github.com/databrickslabs/dlt-meta.git 
+    ```
 
-4. ```cd dlt-meta```
+4. ```commandline
+    cd dlt-meta
+    ```
 
 5. Set python environment variable into terminal
+    ```commandline
+    dlt_meta_home=$(pwd)
     ```
-        export PYTHONPATH=<<local dlt-meta path>>
+    ```commandline
+    export PYTHONPATH=$dlt_meta_home
     ```
 
 6. Run the command ```python demo/launch_dais_demo.py --username=<<your databricks username>> --source=cloudfiles --uc_catalog_name=<<uc catalog name>> --cloud_provider_name=aws --dbr_version=13.3.x-scala2.12 --dbfs_path=dbfs:/dais-dlt-meta-demo-automated_new```

docs/content/demo/Silver_Fanout.md

@@ -17,7 +17,12 @@ draft: false
 1. Launch Terminal/Command prompt 
 
 2. Install [Databricks CLI](https://docs.databricks.com/dev-tools/cli/index.html)
-
+    - Once you install Databricks CLI, authenticate your current machine to a Databricks Workspace:
+
+    ```commandline
+    databricks auth login --host WORKSPACE_HOST
+    ```
+
 3. ```commandline
     git clone https://github.com/databrickslabs/dlt-meta.git 
     ```

docs/content/demo/Techsummit.md

@@ -11,14 +11,26 @@ This demo will launch auto generated tables(100s) inside single bronze and silve
 1. Launch Terminal/Command prompt 
 
 2. Install [Databricks CLI](https://docs.databricks.com/dev-tools/cli/index.html)
+    - Once you install Databricks CLI, authenticate your current machine to a Databricks Workspace:
+
+    ```commandline
+    databricks auth login --host WORKSPACE_HOST
+    ```
 
-3. ```git clone https://github.com/databrickslabs/dlt-meta.git ```
+3. ```commandline
+    git clone https://github.com/databrickslabs/dlt-meta.git 
+    ```
 
-4. ```cd dlt-meta```
+4. ```commandline
+    cd dlt-meta
+    ```
 
 5. Set python environment variable into terminal
+    ```commandline
+    dlt_meta_home=$(pwd)
     ```
-        export PYTHONPATH=<<local dlt-meta path>>
+    ```commandline
+    export PYTHONPATH=$dlt_meta_home
     ```
 
 6. Run the command ```python demo/launch_techsummit_demo.py [email protected] --source=cloudfiles --cloud_provider_name=aws --dbr_version=13.3.x-scala2.12 --dbfs_path=dbfs:/techsummit-dlt-meta-demo-automated ```

docs/content/getting_started/dltmeta_cli.md

@@ -7,6 +7,11 @@ draft: false
 
 ### pre-requisites:
 - [Databricks CLI](https://docs.databricks.com/en/dev-tools/cli/tutorial.html)
+- Once you install Databricks CLI, authenticate your current machine to a Databricks Workspace:
+
+   ```commandline
+   databricks auth login --host WORKSPACE_HOST
+   ```
 - Python 3.8.0 +
 ##### Steps:
 1. ``` git clone https://github.com/databrickslabs/dlt-meta.git ```