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Module 1: Overview and SetUp

Module 1: Data Pod Setup​

Setting up a Data Pod is the first step in onboarding your data for profiling, transformation, and analytics. Follow the guided steps below to configure your Data Pod with the necessary metadata, connections, and context.

Step 1: Launch the Data Pod Setup​

From the Data Pods home screen, click on the + ADD DATA POD button.

Data Pod Selection Screen

This opens up the multi-step setup process.

Step 2: Fill in Data Pod Details​

Enter the Name, Description, Industry, and Location for the Data Pod.

Data Pod Details

These values define the identity of your Data Pod and help categorize it for domain-specific processing.

Step 3: Configure Data Sources​

Add one or more data sources from where your data will be read. Supported options include:

  • Azure Storage Gen2
  • AWS S3
  • GCP Storage
  • Databricks Catalog

Data Sources List

You can click ADD DATASOURCE to create a new connection.

Step 4: Create a Data Source Connection​

Specify the connection name, select the service type, and fill in the required configuration values.

Create Data Source

This enables the platform to securely read raw data from your specified storage layer.

Step 5: Add a Data Lake (Optional)​

Set up a data lake destination where the processed or profiled data will be written.

Data Lake Setup

Click ADD DATALAKE and provide the necessary connection details.

Step 6: Create a Data Lake Connection​

Choose the service (e.g., Azure Storage Gen2 or Microsoft OneLake), and enter the configuration JSON to define your storage endpoint.

Create Data Lake

The data lake acts as the write destination for enriched or intermediate data.

Step 7: Add a Data Warehouse (Optional)​

Set up a data warehouse destination for structured analytics and reporting.

Data Warehouse Setup

Click ADD DATAWAREHOUSE to begin setup.

Step 8: Create a Data Warehouse Connection​

Choose the appropriate service (e.g., Microsoft Fabric, Databricks Catalog), then input your connection credentials and metadata.

Create Data Warehouse

The warehouse is used to write finalized, structured data for BI and reporting use cases.

Step 9: Provide Data System Context​

Select the relevant data domains and provide contextual descriptions for each, helping enrich metadata for profiling and business understanding.

Data Source Context

You can also generate a Context Summary to auto-summarize key information about the data systems.

Data Source Context​

Step 10: Review Summary and Manage Access​

At the final step, review all Data Pod details and click on Manage Access to share it with other users in your organization.

Final Summary and Access

Final Summary and Access

✅ Your Data Pod is now set up and ready!​

You can now proceed to profile, transform, and analyze the data within your configured Data Pod.