Release Notes

August 2026

We've updated the following quickstart data model packages to add DuckDB as a supported destination:

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Ad Reporting to version v2.7.3
Amazon Ads to version v1.3.1
Amazon Selling Partner to version v0.5.1
Amplitude to version v1.4.1
App Reporting to version v1.3.2
Apple App Store to version v1.3.2
Apple Search Ads to version v1.3.1
Asana to version v1.4.1
AWS Cloud Cost to version v0.4.1
Facebook Ads to version v1.5.1
Facebook Pages to version v1.3.1
Fivetran Platform Connector to version v2.5.3
GitHub to version v1.4.1
Google Ads to version v1.4.1
Google Analytics 4 Export to version v0.7.2
Google Play to version v1.3.1
Greenhouse to version v1.4.1
HubSpot to version v1.9.2
Instagram Business to version v1.2.1
Intercom to version v1.7.1
Iterable to version v1.5.1
Jira to version v1.10.2
Klaviyo to version v1.4.1
Lever to version v1.3.1
LinkedIn Ad Analytics to version v1.3.1
LinkedIn Company Pages to version v1.5.1
Mailchimp to version v1.3.2
Marketo to version v1.4.1
Microsoft Advertising to version v1.3.1
Microsoft Dynamics 365 CRM to version v0.4.1
Mixpanel to version v0.17.1
NetSuite SuiteAnalytics to version v1.7.1
Pardot to version v1.4.1
Pendo to version v1.4.1
Pinterest Ads to version v1.3.1
Qualtrics to version v1.3.1
QuickBooks to version v1.9.1
Recharge to version v1.5.2
Recurly to version v1.5.1
Reddit Ads to version v1.5.1
Sage Intacct to version v1.4.1
Salesforce to version v2.4.1
Salesforce Marketing Cloud to version v0.6.1
SAP to version v0.8.1
ServiceNow to version v1.0.2
Shopify to version v1.9.2
Shopify Holistic to version v1.3.1
Snapchat Ads to version v1.3.1
Social Media Reporting to version v1.6.2
StackAdapt to version v0.2.1
Stripe to version v1.10.1
TikTok Ads to version v1.4.1
Twilio to version v1.4.1
Unified RAG to version v0.3.1
Workday HCM to version v1.0.3
X Ads to version v1.3.1
X Organic to version v1.2.1
Xero to version v1.6.1
YouTube Analytics to version v1.2.1
Zendesk Support to version v1.7.1
Zuora to version v1.4.1

June 2026

v0.2.0

Under the Hood

Migrates the union_connections, apply_source_relation, and partition_by_source_relation macros to the dbt_fivetran_utils package.
Adds the fivetran_using_source_casing variable for case-sensitive destination support. When enabled, downstream transformations respect source casing to ensure consistent results. See the Additional Configurations section of the README for details.

May 2026

v0.1.0

This is the initial release of the dbt_stackadapt dbt package.

Initial Release

This package models data from Fivetran's StackAdapt connector and produces the following analytics-ready tables:

Table	Description
`stackadapt__advertiser_report`	Represents daily performance aggregated at the advertiser level, including `impressions`, `clicks`, `spend`, and `conversions`. Example Analytics Questions: How does performance compare across different advertisers? Which advertisers are driving the most spend or conversions?
`stackadapt__campaign_group_report`	Represents daily performance aggregated at the campaign group level, including `impressions`, `clicks`, `spend`, and `conversions`. Example Analytics Questions: Which campaign groups have the highest click-through rate or conversion rate? How does spend and performance compare across campaign groups within each advertiser?
`stackadapt__campaign_report`	Represents daily performance aggregated at the campaign level, including `impressions`, `clicks`, `spend`, and `conversions`. Example Analytics Questions: Which campaigns are most efficient in terms of cost per conversion? How does delivery performance vary by campaign channel type and status?
`stackadapt__ad_report`	Represents daily performance at the individual ad level, including `impressions`, `clicks`, `spend`, and `conversions`. Example Analytics Questions: Which ad creatives are driving the lowest cost per click? How do different ad sizes compare in performance? Which ads are top-performing within each campaign?
`stackadapt__url_report`	Represents daily performance aggregated at the landing URL level, with URL components and UTM parameters parsed from `click_url`. Includes `impressions`, `clicks`, `spend`, and `conversions`. Example Analytics Questions: Which landing pages are driving the most conversions? How does performance compare across UTM campaigns and sources? Which URL paths have the highest spend relative to conversions?