Connectors

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YouTube Analytics

Data replication

Sync YouTube Analytics data anywhere.

A YouTube Analytics is a group that is set of collection of up to 500 channels, videos, playlists, or assets. It aggregate data from competitor specific accounts, videos, and subscribers. As a generator, you can enable to detect the best time to publicize a video, how to increase the engagement of your subscribers, and the interests of the audience by viewing other channel analytics. For better understand your video and channel performance with key metrics and reports in YouTube Studio you can use analytics.

  • Standard
  • Beta
  • 19 streams
Sync YouTube Analytics dataRead the docs
YouTube Analytics

One connector

Everything YouTube Analytics can do in Airbyte

  • Sync to your warehouse

    Land 19 YouTube Analytics tables in 50+ destinations on a schedule you control.

    Sync to your warehouse

    Land 19 YouTube Analytics tables in 50+ destinations on a schedule you control.

  • Incremental syncs

    Pull only the records that changed since the last run instead of reloading everything.

    Incremental syncs

    Pull only the records that changed since the last run instead of reloading everything.

  • Cloud or self-hosted

    Run the YouTube Analytics connector on Cloud, Self-Managed Enterprise.

    Cloud or self-hosted

    Run the YouTube Analytics connector on Cloud, Self-Managed Enterprise.

Specifications

What to know before you sync YouTube Analytics

  • Support levelStandard
  • Available onCloud, Self-Managed Enterprise
  • Connector version1.4.2
  • Release stageBeta

Sync capabilities

  • Full Refresh SyncSupported
  • Incremental SyncSupported
  • Destinations50+ Airbyte connectors

Set up in 10 steps

  1. Go to the YouTube Analytics website and sign in to your account.
  2. Click on your profile picture in the top right corner and select "YouTube Studio".
  3. In the left-hand menu, click on "Settings" and then "Channel".
  4. Scroll down to the "Advanced settings" section and click on "View API key".
  5. Click on "Create API key" and copy the key that is generated.
  6. Go to the Airbyte dashboard and click on "Sources" in the left-hand menu.
  7. Click on "New Source" and select "YouTube Analytics" from the list of available connectors.
  8. Enter a name for your source and paste the API key you copied earlier into the "API Key" field.
  9. Click on "Test Connection" to ensure that the credentials are valid and the connection is successful.
  10. Once the connection is successful, click on "Create Source" to save your settings and start syncing your data.

19 streams

Every table you can sync from YouTube Analytics

  • report_types

  • channel_annotations_a1

  • channel_basic_a3

  • channel_cards_a1

  • channel_combined_a3

  • channel_demographics_a1

  • channel_device_os_a3

  • channel_end_screens_a1

  • channel_playback_location_a3

  • channel_province_a3

  • channel_sharing_service_a1

  • channel_subtitles_a3

  • channel_traffic_source_a3

  • playlist_basic_a2

  • playlist_combined_a2

  • playlist_device_os_a2

  • playlist_playback_location_a2

  • playlist_province_a2

  • playlist_traffic_source_a2

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Common questions

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ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

YouTube Analytics API provides access to a wide range of data related to YouTube channels and videos. The API allows developers to retrieve data on channel performance, video engagement, and audience demographics. Here are the categories of data that the YouTube Analytics API provides:

1. Channel data: This includes data related to the channel's views, subscribers, and watch time.
2. Video data: This includes data related to individual videos, such as views, likes, dislikes, comments, and shares.
3. Audience data: This includes data related to the demographics of the channel's audience, such as age, gender, and location.
4. Playback locations: This includes data related to where the videos are being played, such as on YouTube, embedded on other websites, or on mobile devices.
5. Traffic sources: This includes data related to how viewers are finding the channel's videos, such as through search, suggested videos, or external websites.
6. Ad performance: This includes data related to the performance of ads on the channel, such as impressions, clicks, and revenue.
7. Engagement data: This includes data related to how viewers are engaging with the channel's videos, such as watch time, average view duration, and audience retention.

1. Go to the YouTube Analytics website and sign in to your account.
2. Click on your profile picture in the top right corner and select "YouTube Studio".
3. In the left-hand menu, click on "Settings" and then "Channel".
4. Scroll down to the "Advanced settings" section and click on "View API key".
5. Click on "Create API key" and copy the key that is generated.
6. Go to the Airbyte dashboard and click on "Sources" in the left-hand menu.
7. Click on "New Source" and select "YouTube Analytics" from the list of available connectors.
8. Enter a name for your source and paste the API key you copied earlier into the "API Key" field.
9. Click on "Test Connection" to ensure that the credentials are valid and the connection is successful.
10. Once the connection is successful, click on "Create Source" to save your settings and start syncing your data.

The most prominent ETL tools to transfer data to include: Airbyte, Fivetran, StitchData, Matillion, Talend Data Integration. These tools help in extracting data from various sources (APIs, databases, and more), transforming it efficiently, and loading it into and other databases, data warehouses and data lakes, enhancing data management capabilities.

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

Start moving YouTube Analytics data today

Free for 14 days on Airbyte Cloud. Set up the YouTube Analytics connector once and let Airbyte keep it in sync.

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