Home > Destinations > Snowflake > Youtube Analytics

Connect Youtube Analytics to Snowflake

Connect Youtube Analytics to Snowflake and export selected accounts, metrics, and dimensions to your Google BigQuery project.

Configure the historical window, destination table, and recurring schedule without maintaining a Youtube Analytics API pipeline.

Youtube Analytics export job

First sync scheduled

Youtube Analytics Selected accounts

Configured job

Snowflake Destination table

Account Youtube Analytics · Client group A

Table daily_dump

Initial import Configured historical window

Schedule Daily · 06:00 UTC

Fields Selected metrics + dimensions

Partition date · eligible field

Illustrative job · configure values for your account Export ready

Used by the world's leading companies

Export Youtube Analytics data to Snowflake

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Youtube Analytics data in PostgreSQL

Bring all your Youtube Analytics data into your warehouse and make it available for analytics, machine learning, and internal applications.

Source

Youtube Analytics Social data

INaccounts PMprofiles CUposts BLmedia

Catchr pipeline IN PM CU Extract · normalize · load

Snowflake catchr_data.Youtube Analytics_raw

TableScopeStatus

accountsSelectedReady

profilesSelectedReady

postsSelectedReady

mediaSelectedReady

Data freshness

Keep your Snowflake tables up to date

Automatically sync new data from Youtube Analytics so every dashboard, model, and report works with fresh information.

Youtube AnalyticsConfigured account

SnowflakeYoutube Analytics Metrics_raw

Rows processed Scheduled loads Example 24h

00:0006:0012:0018:00

Latest run Completed 06:00 UTC

New rows +428 4 tables updated

Next run Scheduled 12:00 UTC

accounts326 updated profiles102 appended Warehouse up to date

Analysis

Unify Youtube Analytics with the rest of your business data

Join marketing, finance, CRM, and product data inside the same warehouse.

Business data model

model / business_360

Warehouse inputs

QuickBooks accounts · Ad Impressions Social

Marketingcampaign · spend · UTM Ads

CRMcontact_id · lifecycle Sales

Productaccount_id · event_date Usage

Match keys customer · date · campaign

Snowflake model business_360 Unified

FieldFrom

customer_idCRM

Ad Impressionsaccounts

ad_spendMarketing

lifecycle_stageCRM

active_usersProduct

Ready for SQL 5 business fields

Youtube Analytics metrics and dimensions available in Snowflake

Access 36 metrics and 180 dimensions from Youtube Analytics connectors including Views, Estimated Minutes Watched, Average View Duration, Subscribers Gained, Estimated Revenue, Date, Country, Device Type, Insight Traffic Source Type, Subscribed Status and many more...

Metrics availables

180

Dimensions availables

View all Youtube Analytics Metrics metrics and dimensions

Connect Youtube Analytics to Snowflake in minutes

Move your data from Youtube Analytics to Snowflake with a simple setup. Once connected, Catchr handles the ingestion automatically so your warehouse stays up to date without manual work.

Step one

Connect your Youtube Analytics account

Authenticate your Youtube Analytics account securely in Catchr. No custom scripts, API maintenance, or engineering work required.

Connect now

Client A · Connected sources

5 sources ready

Youtube Analytics 3 advertising accounts Connected

Google Ads 2 advertising accounts Connected

Google Analytics 4 1 web property Connected

HubSpot 1 CRM portal Connected

Step two

Choose the Snowflake destination

Add the account host, user, and database schema. Use a password for compatible users or a PEM private key for service accounts and stricter policies.

Destination / Snowflake Required fields

Authentication Choose one

Password

Key pair

Host Required

xy12345.eu-west-1

Username Required

catchr_service

Database Required

MARKETING.RAW

Private key passphrase Optional

••••••••••••

Private key Required for key pair

-----BEGIN ENCRYPTED PRIVATE KEY----- MIIE6TAbBgkqhkiG9w0BBQMw... -----END ENCRYPTED PRIVATE KEY-----

Step three

Keep your Snowflake tables updated

Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your PostgreSQL table.

Export job / PostgreSQL Example

Schema Destination

marketing_raw

Table Per job

linkedin_ads_daily

Recurring schedule Choose a cadence

Every 6 hours

Daily · 07:00

Weekly · Mon

First sync scheduledSelected fields · configured history

07:00 UTC

Review 30-day Youtube Analytics organic content performance in SQL.

This example summarizes impressions, reach, engagements, and engagement rate by post.

30-day window

SELECT
  post_id,
  SUM(impressions) AS impressions,
  SUM(reach) AS reach,
  SUM(engagements) AS engagements,
  SAFE_DIVIDE(
    SUM(engagements),
    SUM(impressions)
  ) AS engagement_rate
FROM `your_project.marketing_raw.youtube_analytics_content_daily`
WHERE date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY post_id
ORDER BY engagements DESC;

Illustrative SQL — adapt it to the fields and schema selected in your export. Standard SQL

Choose what to load into Snowflake.

Each connector has its own entities, fields, historical limits, and reporting uses. Open a source page for the details that belong to that platform.

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Emailing

Before you schedule the job.

Answers about PostgreSQL setup, available source data, schedules, table updates, and SQL use cases.

Can Catchr send Youtube Analytics records directly to Snowflake?

Add Youtube Analytics in Sources and connect the existing Snowflake database in Storage. A datastream defines the route, while the job loads the chosen fields into "media".

How much control do I have over Youtube Analytics fields in Snowflake?

Select concrete Youtube Analytics fields such as Ad Impressions, Annotation Click Through Rate, Annotation Clickable Impressions, and Date. You can rename the chosen columns, preview the result, and write them to Snowflake tables such as accounts, profiles, and posts.

How should I configure recurring Youtube Analytics imports in Snowflake?

Define the first Youtube Analytics fetch, run frequency, and lookback window in the "media" job. Each scheduled run replaces data inside the configured period.

How do I prevent duplicate Youtube Analytics rows in Snowflake?

Use a supported date field to partition "media". Recurring Youtube Analytics runs can then update the selected window instead of adding another copy of the same period.

How can a team use Youtube Analytics data after it reaches Snowflake?

With Youtube Analytics data, a Snowflake query can summarize impressions, reach, engagements, and engagement rate by post. Model Ad Impressions and Annotation Click Through Rate in SQL, then expose the result to dashboards, internal tools, or recurring client reports.

Does my Snowflake database need to exist before I connect it?

Yes. Connect an existing Snowflake database first. The Catchr job creates and populates the destination table you configure inside that database.

Can I load several marketing sources into the same Snowflake database?

Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.

Still have a question ?

Our teams is always here to responds to any question you could have about our data connector.

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100+ sources

Used by the world's leading companies

Export Youtube Analytics data to Snowflake

Centralize Youtube Analytics data in PostgreSQL

Keep your Snowflake tables up to date

Unify Youtube Analytics with the rest of your business data

Youtube Analytics metrics and dimensions available in Snowflake

Connect Youtube Analytics to Snowflake in minutes

Connect your Youtube Analytics account

Choose the Snowflake destination

Keep your Snowflake tables updated

Review 30-day Youtube Analytics organic content performance in SQL.

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