Create Data Products Using Getting Started Wizard

Alation Cloud Service Applies to Alation Cloud Service instances of Alation

The Getting Started Wizard provides a guided 4-step workflow that helps you create data products quickly using AI-powered assistance. The wizard reduces data product creation time from 20+ minutes to under 5 minutes by automating content generation and providing structured guidance.

Important

The Getting Started Wizard automatically generates business context, example questions, and product details based on your selected data assets, making it easier for both technical and non-technical users to create comprehensive data products.

In this topic:

Understanding the Getting Started Wizard

The Getting Started Wizard is designed to streamline data product creation through a structured approach that leverages AI assistance and existing catalog metadata.

Key Benefits

  • AI-Powered Content Generation: Automatically generates business context and example questions based on your selected data assets

  • Draft Support: Save progress at any step and resume later without losing work

  • Guided Process: Step-by-step workflow prevents common setup errors

  • Quick Setup: Complete data product creation in under 5 minutes

  • Accessibility: Full keyboard navigation and screen reader support

When Data Products Are Created

Understanding when your data product is created is important for managing your workflow:

  • A draft data product is created when you click Next on Step 1 (Set Up Data Product)

  • Before clicking Next on Step 1, no data product exists in the system

  • All new data products are private by default until explicitly shared

  • Draft products appear in My Data Products with a “Draft” indicator

  • Once created, you can save progress and resume from any step

Accessing the Wizard

There are two ways to access the Getting Started Wizard:

From Data Products App Navigation:

  1. In the Data Products App, expand the left-side navigation panel

  2. Click + New next to My Data Products

From Manage My Data Products:

  1. Navigate to My Data Products in the left-side navigation

  2. Click + Add Data Product in the top-right corner

The wizard opens in a full-screen dialog with a progress indicator showing the current step.

Step 1: Set Up Data Product

The first step establishes the foundation of your data product with basic information that guides AI generation in later steps.

Required Information

Data Product Name

Enter a unique, descriptive name for your data product. The system automatically generates a URL-friendly slug from this name. If you leave the name empty, it defaults to “New Data Product”.

Description (What you want to build)

Provide a clear description of what you want to build with this data product. This description is crucial as it helps the AI generate better business context and example questions in Step 3. Focus on:

  • The business problem you’re solving

  • What insights users should gain

  • How the data product will be used

Optional Features

Add Table

You can optionally select an initial table to include in your data product. If you choose a table here:

  • It automatically carries forward to Step 2

  • The column selection dialog opens automatically in Step 2

  • This provides a starting point for your data assets

Exit Behavior in Step 1

The exit behavior changes based on whether you’ve created the data product:

Before Creation (before clicking Next):

  • Button shows Discard

  • Clicking Discard removes all progress without creating a product

  • This is the only point where you can exit without creating anything

After Creation (after navigating back to Step 1):

  • Button shows Save and Exit

  • Clicking Save and Exit saves current progress as a draft

  • Product remains visible in My Data Products

Creating the Data Product

When you click Next after filling the required information:

  1. The data product is created with “Draft” status

  2. It becomes visible in My Data Products with a draft indicator

  3. The wizard progresses to Step 2 (Add Data Assets)

  4. You can now save progress at any point and resume later

Step 2: Add Data Assets

Step 2 focuses on selecting and configuring the tables and columns that will be part of your data product.

Search and Select Tables

Table Search Interface:

Use the search bar to find relevant tables from your data catalog. The search includes:

  • Table names and descriptions

  • Popularity metrics to help identify commonly used tables

  • Metadata from the Alation catalog

Recommended Tables:

Based on your Step 1 description, the system may suggest recommended tables that align with your data product’s purpose. These suggestions help you discover relevant data assets you might not have considered.

Adding Tables:

  1. Search for tables using descriptive keywords

  2. Review table information including descriptions and popularity

  3. Click Add to include tables in your data product

  4. Repeat the process to add multiple tables

Column Selection and Configuration

For each selected table, you can configure column-level details:

Column Selection:

  • Choose specific columns rather than including entire tables

  • Select only the columns relevant to your data product’s purpose

  • Use the Select All option if all columns are needed

Column Metadata:

  • View existing descriptions and data types from the catalog

  • Generate missing descriptions using AI assistance

  • Review popularity metrics to understand column usage

Access Configuration:

Configure access permissions for each table:

  • Set appropriate access levels based on data sensitivity

  • Define who can view or use each table

  • Specify any special access requirements

Managing Selected Tables

The Selected Tables panel shows your current selections:

  • Review all selected tables and their column counts

  • Remove tables that are no longer needed

  • Modify column selections for existing tables

  • View access configurations at a glance

Multiple Table Support:

You can add as many tables as needed for your data product. Each table maintains its own column selection and access configuration, allowing for granular control over what data is included.

Step 3: Add Business Context

Step 3 leverages AI to generate meaningful business context based on your selected data assets from Steps 1 and 2.

AI Generation Process

The AI generation happens automatically when you reach Step 3:

  1. Context Analysis: The system analyzes your product description and selected data assets

  2. Content Generation: AI generates business context and example questions (typically takes under 15 seconds)

  3. Display Results: Generated content appears with editing capabilities

Generated Content Elements

Business Context:

  • Detailed explanation of the business value and use cases

  • Context about how the data product supports decision-making

  • Information about the relationship between different data assets

  • Relevant business definitions and assumptions

Example Questions:

  • Sample questions that users can answer with this data product

  • Business scenarios where the data product provides value

  • Analytical use cases supported by the selected data assets

Editing and Customization

All AI-generated content is fully editable:

Rich Text Editing:

  • Use the markdown-supported editor to refine content

  • Add formatting, links, and structured information

  • Include organization-specific terminology or context

Managing Example Questions:

  • Edit existing questions to better match your use cases

  • Add new questions based on known business needs

  • Remove questions that aren’t relevant to your audience

  • Use the Add Question button to include additional examples

Regeneration Options:

If the AI-generated content doesn’t meet your needs:

  • Use the Regenerate button to create new content

  • Edit the content manually to better match your requirements

  • Combine AI suggestions with your own domain expertise

Note

The business context and example questions are important for helping data consumers understand the value and potential uses of your data product. Take time to review and refine this content to ensure it accurately represents your data product’s purpose.

Step 4: Finalize Product Details

The final step completes your data product with comprehensive metadata and prepares it for publication.

AI-Generated Product Details

Like Step 3, Step 4 uses AI to generate final product elements based on all previous steps:

Summary:

A concise executive summary that captures the key value proposition of your data product

Enhanced Description:

An expanded version of your initial description that incorporates context from your selected data assets

Icon Generation:

A visual identifier created based on your product description that represents the theme and purpose of your data product

URL Slug:

A unique, web-friendly identifier automatically generated from your product name with validation for uniqueness

Auto-Populated Information

Certain fields are automatically populated from your Alation profile:

Contact Information:

  • Your name appears as the default contact name

  • Your email is set as the contact email for access requests

  • Your profile avatar becomes the default product contact image

Permissions:

  • You’re automatically assigned as the product administrator

  • You have full editing and management permissions

  • You can grant additional permissions to team members later

Customization and Review

Before publishing, review and customize the generated content:

Product Name:

  • Override AI suggestions if needed

  • Ensure the name clearly represents your data product

  • Verify it’s unique and follows your organization’s naming conventions

Summary and Description:

  • Edit the generated summary to ensure accuracy

  • Add organization-specific information or requirements

  • Include any compliance or governance notes

Icon Selection:

  • Review the AI-generated icon

  • Choose from alternative suggestions if available

  • Ensure the icon appropriately represents your data product

Slug Validation:

  • The system checks slug uniqueness in real-time

  • Automatic suggestions are provided for conflicts (e.g., product-name-1)

  • You can modify the slug while maintaining URL compatibility

Contact Verification:

  • Confirm contact information is correct and up-to-date

  • Add additional contact methods if needed

  • Verify the contact information matches your organization’s standards

Managing Drafts and Progress

The Getting Started Wizard includes comprehensive draft management to support interrupted workflows.

Save and Exit Functionality

Available on All Steps (after Step 1 creation):

The Save and Exit button is available on Steps 2-4 and on Step 1 after the data product has been created.

What Gets Saved:

  • All form inputs and selections from previous steps

  • Current step progress and validation state

  • Selected tables, columns, and access configurations

  • Any AI-generated content and user modifications

Draft Storage:

  • Drafts are saved to your Alation instance

  • Progress persists across browser sessions

  • Multiple drafts can exist simultaneously

Resuming Work

Finding Your Drafts:

  1. Navigate to My Data Products in the Data Products app

  2. Look for products with a “Draft” status indicator

  3. Draft products display the product name (or “New Data Product” if unnamed)

Resuming the Wizard:

  1. Click the Edit button next to your draft product

  2. The Getting Started Wizard reopens at the step where you left off

  3. All previous progress and selections are preserved

  4. Continue from where you stopped

Draft Management:

  • Edit draft product names directly in the My Data Products grid

  • Delete drafts that are no longer needed

  • Monitor draft creation dates to track progress over time

Publishing Your Data Product

Completing the wizard transforms your draft into a published data product.

Final Review

Before clicking Finish in Step 4, review:

  • Product Name and Description: Ensure they accurately represent your data product

  • Selected Data Assets: Verify all necessary tables and columns are included

  • Business Context: Confirm the context and example questions are helpful for users

  • Contact Information: Check that contact details are correct and current

  • Access Instructions: Review any automatically generated access configurations

Publishing Process

When you click Finish:

  1. Validation: The system validates your data product configuration

  2. Status Change: The product status changes from “Draft” to “Published”

  3. Marketplace Listing: The data product becomes discoverable in the marketplace (if configured)

  4. Catalog Integration: Full catalog page becomes available with all configured features

After Publishing

Once published, your data product:

  • Appears in Search Results: Users can discover it through marketplace search

  • Enables Access Requests: Users can request access through configured delivery systems

  • Supports Chat Features: AI chat capabilities become available (if configured)

  • Provides Full Functionality: All data product features are active

Continued Editing:

After publishing, you can continue to edit and enhance your data product:

  • Use the full data product editor (not the wizard)

  • Add additional metadata, metrics, or mock data

  • Configure advanced features like delivery systems

  • Update business context as requirements evolve

Version Management:

While Alation doesn’t currently support automatic version history, you can:

  • Manage versions externally if needed

  • Document significant changes in the product description

  • Communicate updates to data product consumers

Note

Once you complete the Getting Started Wizard, re-opening the data product will use the standard data product editor interface, not the wizard. The wizard is specifically designed for initial creation workflows.

Troubleshooting and Best Practices

Common Issues and Solutions

Slow AI Generation:

  • Wait up to 15 seconds for content generation to complete

  • Use the Regenerate button if content doesn’t appear

  • Edit content manually if AI generation isn’t suitable for your needs

Table Search Problems:

  • Use more specific search terms related to your domain

  • Check spelling and try alternative keywords or synonyms

  • Contact your Alation administrator if expected tables don’t appear

Slug Conflicts:

  • The system automatically suggests alternatives (e.g., product-name-1)

  • Choose a more unique product name to avoid conflicts

  • Modify the suggested slug while maintaining URL compatibility

Draft Issues:

  • Refresh the browser if draft data doesn’t load properly

  • Clear browser cache if experiencing persistent issues

  • Contact support if drafts become corrupted or inaccessible

Best Practices for Success

Step 1 Optimization:

  • Provide detailed, specific descriptions to improve AI generation quality

  • Use business terminology that your target audience will understand

  • Focus on the value and outcomes rather than technical implementation details

Data Asset Selection:

  • Choose tables that directly support your defined use cases

  • Select only relevant columns to keep the data product focused

  • Consider data sensitivity and access requirements when making selections

Business Context Enhancement:

  • Review AI-generated content for accuracy and completeness

  • Add organization-specific context and terminology

  • Include practical examples that resonate with your user base

  • Ensure example questions reflect real analytical scenarios

Final Review Process:

  • Test access request processes before publishing

  • Verify all contact information is current and monitored

  • Confirm the data product name and description clearly communicate value

  • Review all configurations for accuracy and completeness

Tip

The Getting Started Wizard is designed to create a solid foundation in under 5 minutes. After publishing, you can always enhance your data product with additional features using the full editor interface, including metrics, advanced access controls, and detailed mock data.

Getting Help

If you encounter issues while using the Getting Started Wizard:

  • Use the Regenerate button for AI content that doesn’t meet your needs

  • Edit any generated content manually to better match your requirements

  • Consult your organization’s data governance guidelines for naming and content standards

  • Contact your Alation administrator for technical issues or missing catalog data

  • Refer to Get Started with Creating Data Products for advanced configuration options