Model IDE orientation

Omni does a lot of work on your behalf to understand how to navigate your database. This allows for both accelerated initial deployments and long term scalability as the underlying schema changes. You will notice that several files are automatically generated when you connect your database and initialize a data model. This section will walk through the different types of files in the model and orient you on how to use them.

Part 1: Model IDE basics

Start with learning about the key features of Omni's modeling IDE, which offers powerful tools for managing data models at scale.

In this video, you'll learn about:

• Files in the IDE, such as models, relationships, topics, and views
• Development tools such as branching and version control
• The content validator, which identifies and fixes errors across dashboards and workbooks
• The dbt IDE, which provides a read-only view of dbt projects

Part 2: Model files

Explore the powerful customization options within Omni's model file to curate experiences for your end users. Model files are used to define configuration for the analytical environment (topics, views, and so on) associated with a specific connection.

In this video, you'll learn to:

• Streamline navigation and reduce complexity by including and excluding schemas, views, and fields
• Utilize access grants to restrict user access to topics and fields based on user attributes to
• Balance performance and data freshness with caching policies

Part 3: Relationships file

Enable your users to explore data without fear of disruption by utilizing the relationship management file. In this file, you can pre-define joins and automatically propagate them to workbook queries, thus removing the need for manual updates.

In this video, you'll learn to:

• Define relationships between tables using Omni's YAML syntax and the workbook
• Specify relationship types and direction
• Create advanced custom joins with SQL logic, table aliases, and filters

Part 4: View files

Define what users see when accessing tables in the workbook by customizing the table's view file.

In this video, you'll learn to:

• Improve discovery with metadata such as labels, descriptions, tags, and field groups
• Refine the data by adding filters and including or excluding specific fields
• Encourage deeper exploration with drill fields

Part 5: Topic files

Curate an entire dataset by using topics, which allow you to organize and structure data around a specific area of interest or analysis.

In this video, you'll learn to:

• Refine the dataset by specifying which tables and fields to include
• Define pre-configured filters to apply to workbook queries
• Improve Blobby AI's understanding of the topic by providing context