The core concepts of AI Squared are the foundation of your data journey. They include Sources, Destinations, Models, and Syncs. Understanding these concepts is crucial to building a robust data pipeline.

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Sources: The Foundation of Data

Overview

Sources are the starting points of your data journey. It’s where all your data is stored and where AI Squared pulls data from.

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These can be:

  • Data Warehouses: For example, Snowflake Google BigQuery and Amazon Redshift
  • Databases and Files: Including traditional databases, CSV files, SFTP

Adding a Source

To integrate a source with AI Squared, navigate to the Sources overview page and select ‘Add source’.

Destinations: Where Data Finds Value

Overview

‘Destinations’ in AI Squared are business tools where you want to send your data stored in sources.

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These can be:

  • CRM Systems: Like Salesforce, HubSpot, etc.
  • Advertising Platforms: Such as Google Ads, Facebook Ads, etc.
  • Marketing Tools: Braze and Klaviyo, for example

Integrating a Destination

Add a destination by going to the Destinations page and clicking ‘Add destination’.

Models: Shaping Your Data

Overview

‘Models’ in AI Squared determine the data you wish to sync from a source to a destination. They are the building blocks of your data pipeline.

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They can be defined through:

  • SQL Editor: For customized queries
  • Visual Table Selector: For intuitive interface
  • Existing dbt Models or Looker Looks: Leveraging pre-built models

Importance of a Unique Primary Key

Every model must have a unique primary key to ensure each data entry is distinct, crucial for data tracking and updating.

Syncs: Customizing Data Flow

Overview

‘Syncs’ in AI Squared helps you move data from sources to destinations. They help you in mapping the data from your models to the destination.

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There are two types of syncs:

  • Full Refresh Sync: All data is synced from the source to the destination.
  • Incremental Sync: Only the new or updated data is synced.