# Leverage Warehouse Data in Audiences ### About this export | Field | Value | | --- | --- | | **content_type** | lesson | | **platform** | contentstack-academy | | **source_url** | https://www.contentstack.com/academy/courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--leverage-warehouse-data-in-audiences | | **course_slug** | data-insights-using-profiles-to-power-personalization | | **lesson_slug** | data-insights-course-4--leverage-warehouse-data-in-audiences | | **markdown_file_url** | /academy/md/courses/data-insights-using-profiles-to-power-personalization/data-insights-course-4--leverage-warehouse-data-in-audiences.md | | **generated_at** | 2026-04-28T06:55:50.212Z | > Part of **[Using Profiles to Power Personalization](https://www.contentstack.com/academy/courses/data-insights-using-profiles-to-power-personalization)** on Contentstack Academy. **Academy MD v3** — structured for retrieval; no quiz or assessment keys. #### Video details #### At a glance - **Title:** 26-data-insights-cloud-connect-audiences - **Duration:** 56s - **Media link:** https://cdn.jwplayer.com/previews/ti1OfDR6 - **Publish date (unix):** 1752893441 #### Streaming renditions - application/vnd.apple.mpegurl - audio/mp4 · AAC Audio · 114446 kbps - video/mp4 · 180p · 180p · 140379 kbps - video/mp4 · 270p · 270p · 154849 kbps - video/mp4 · 360p · 360p · 153389 kbps - video/mp4 · 406p · 406p · 158945 kbps - video/mp4 · 540p · 540p · 177952 kbps - video/mp4 · 720p · 720p · 205252 kbps - video/mp4 · 1080p · 1080p · 287467 kbps #### Timed text tracks (delivery) - **thumbnails:** `https://cdn.jwplayer.com/strips/ti1OfDR6-120.vtt` #### Transcript Cloud Connect audiences or audiences that are built on Cloud Connect data, all of your rules, all of your Cloud Connect attributes are going to be under custom rules. They just get prefixed with CC underscore under the hood. So the other day when we were meeting and we went through and pulled that big query data in to create the first name, last name, and pull in the annual revenue, all of that data lives and exists on the profiles. It functions just like a normal attribute. So this is where you would then go and build an audience. You can combine them with the sort of standard streamed attributes versus the Cloud Connect ones. #### Subtitles (WebVTT) ```webvtt WEBVTT 1 00:00:00.000 --> 00:00:20.000 Cloud Connect audiences or audiences that are built on Cloud Connect data, 2 00:00:20.000 --> 00:00:21.440 all of your rules, 3 00:00:21.440 --> 00:00:24.200 all of your Cloud Connect attributes are going to be under custom rules. 4 00:00:24.200 --> 00:00:28.040 They just get prefixed with CC underscore under the hood. 5 00:00:28.040 --> 00:00:31.880 So the other day when we were meeting and we went through and pulled that big query data in 6 00:00:31.880 --> 00:00:35.480 to create the first name, last name, and pull in the annual revenue, 7 00:00:35.480 --> 00:00:38.040 all of that data lives and exists on the profiles. 8 00:00:38.040 --> 00:00:40.680 It functions just like a normal attribute. 9 00:00:40.680 --> 00:00:43.000 So this is where you would then go and build an audience. 10 00:00:43.000 --> 00:00:47.080 You can combine them with the sort of standard streamed attributes versus the Cloud Connect ones. ``` ```transcript [00:00] Cloud Connect audiences or audiences that are built on Cloud Connect data, [00:20] all of your rules, [00:21] all of your Cloud Connect attributes are going to be under custom rules. [00:24] They just get prefixed with CC underscore under the hood. [00:28] So the other day when we were meeting and we went through and pulled that big query data in [00:31] to create the first name, last name, and pull in the annual revenue, [00:35] all of that data lives and exists on the profiles. [00:38] It functions just like a normal attribute. [00:40] So this is where you would then go and build an audience. [00:43] You can combine them with the sort of standard streamed attributes versus the Cloud Connect ones. ``` #### Key takeaways - Connect **Leverage Warehouse Data in Audiences** back to your stack configuration before moving to the next module. - Capture one concrete artifact (screenshot, Postman call, or code snippet) that proves the step works in your environment. - Re-read the delivery versus management boundary for anything you changed in the entry model. ## Supplement for indexing ### Content summary Leverage Warehouse Data in Audiences. Leverage Warehouse Data in Audiences in Using Profiles to Power Personalization (data-insights-using-profiles-to-power-personalization). ### Retrieval tags - Leverage - Warehouse - Data - Audiences - data-insights-using-profiles-to-power-personalization - lesson 03 - Leverage Warehouse Data in Audiences - data-insights-using-profiles-to-power-personalization lesson ### Indexing notes Index this lesson as a primary chunk tagged with lesson_id "03" and topics: [Leverage, Warehouse, Data, Audiences]. Parent course slug: data-insights-using-profiles-to-power-personalization. Use asset_references URLs as thumbnail hints in search results when present. Never surface LMS quiz content or assessment answers from this file. ### Asset references | Label | URL | | --- | --- | | Video thumbnail: Leverage Warehouse Data in Audiences | `https://cdn.jwplayer.com/v2/media/ti1OfDR6/poster.jpg?width=720` | ### External links | Label | URL | | --- | --- | | Contentstack Academy home | `https://www.contentstack.com/academy/` | | Training instance setup | `https://www.contentstack.com/academy/training-instance` | | Academy playground (GitHub) | `https://github.com/contentstack/contentstack-academy-playground` | | Contentstack documentation | `https://www.contentstack.com/docs/` |