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Connect Google Analytics to Azure SQL

Connect Google Analytics to Azure SQL and export selected accounts, metrics, and dimensions to your Azure SQL project.

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

Google Analytics export job

First sync scheduled

Google Analytics Selected accounts

Configured job

Azure SQL Destination table

Account Google 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 Google Analytics data to Azure SQL

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Google Analytics data in Azure SQL

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

Source

Google Analytics Analytics data

INproperties PMsessions CUusers BLpages

Catchr pipeline IN PM CU Extract · normalize · load

Azure SQL catchr_data.Google Analytics_raw

TableScopeStatus

propertiesSelectedReady

sessionsSelectedReady

usersSelectedReady

pagesSelectedReady

Data freshness

Keep your AzureSQL tables up to date

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

Google AnalyticsConfigured account

AzureSQLGoogle 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

properties326 updated sessions102 appended Warehouse up to date

Analysis

Unify Google 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 properties · 1-day active users Analytics

Marketingcampaign · spend · UTM Ads

CRMcontact_id · lifecycle Sales

Productaccount_id · event_date Usage

Match keys customer · date · campaign

AzureSQL model business_360 Unified

FieldFrom

customer_idCRM

1-day active usersproperties

ad_spendMarketing

lifecycle_stageCRM

active_usersProduct

Ready for SQL 5 business fields

Google Analytics metrics and dimensions available in Azure SQL

Access 81 metrics and 207 dimensions from Google Analytics connectors including Sessions, Active users, Conversions, Total revenue, Engagement rate, Return on ad spend, Session source / medium, Session campaign, Default channel group, Google Ads campaign, Region, Month of the year and many more...

Metrics availables

207

Dimensions availables

View all Google Analytics Metrics metrics and dimensions

Connect Google Analytics to Azure SQL in minutes

Move your data from Google Analytics to Azure SQL 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 Google Analytics account

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

Connect now

Client A · Connected sources

5 sources ready

Google 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 AzureSQL destination

Enter the Azure SQL server host, database, and login details. Catchr verifies the destination before any marketing data is exported.

Destination / Azure SQL Required fields

Host Required

catchr-reporting.database.windows.net

Username Required

catchr_loader

Password Required

••••••••••••

Database Required

marketing_reporting

Step three

Keep your AzureSQL tables updated

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

Export job / Azure SQL Example

Schema Destination

dbo

Table Per job

meta_ads_daily

Recurring schedule Choose a cadence

Every 6 hours

Daily · 06:00

Weekly · Mon

Export readySelected fields · configured history

Every 6 hours

Review 30-day Google Analytics traffic and conversion performance in SQL.

This example summarizes users, sessions, conversions, and conversion rate by traffic source.

30-day window

SELECT
  traffic_source,
  SUM(active_users) AS active_users,
  SUM(sessions) AS sessions,
  SUM(conversions) AS conversions,
  SAFE_DIVIDE(
    SUM(conversions),
    SUM(sessions)
  ) AS conversion_rate
FROM `your_project.marketing_raw.google_analytics_events_daily`
WHERE date >= DATE_SUB(
  CURRENT_DATE(),
  INTERVAL 30 DAY
)
GROUP BY traffic_source
ORDER BY sessions DESC;

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

Connect more table to your Google Analytics data

Open the dedicated route for each platform. Its field catalog, reporting grain, historical constraints, and warehouse use cases should be specific to that source.

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Finance

Before you schedule the job.

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

What do I need to export Google Analytics data to Azure SQL?

Register Google Analytics, save the Azure SQL connection details, and pair both systems in a datastream. The associated job previews and writes the selected columns to "pages".

What does a Google Analytics table in Azure SQL contain?

Select concrete Google Analytics fields such as 1-day active users, 28-day active users, 7-day active users, and Normalized Year. You can rename the chosen columns, preview the result, and write them to Azure SQL tables such as properties, sessions, and users.

How do scheduled Azure SQL jobs keep Google Analytics data current?

The "pages" job can begin with a historical Google Analytics fetch and continue on a recurring schedule. Available history and frequency depend on the source API and your plan.

What controls row replacement in a Google Analytics Azure SQL table?

Select a valid date field when configuring the Google Analytics job for "pages". Catchr deletes and rewrites the scheduled window, limiting duplicate rows across overlapping runs.

How can I model Google Analytics performance with Azure SQL?

With Google Analytics data, an Azure SQL query can summarize users, sessions, conversions, and conversion rate by traffic source. Turn 1-day active users and 28-day active users into a stable Azure SQL view that analysts and reporting tools can query repeatedly.

Does my Azure SQL database need to exist before I connect it?

Yes. Connect an existing Azure SQL 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 Azure SQL 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.

Used by the world's leading companies

Export Google Analytics data to Azure SQL

Centralize Google Analytics data in Azure SQL

Keep your AzureSQL tables up to date

Unify Google Analytics with the rest of your business data

Google Analytics metrics and dimensions available in Azure SQL

Connect Google Analytics to Azure SQL in minutes

Connect your Google Analytics account

Choose the AzureSQL destination

Keep your AzureSQL tables updated

Review 30-day Google Analytics traffic and conversion performance in SQL.

Connect more table to your Google Analytics data

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Bigcommerce

Youtube Analytics

Google Ads

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Facebook Pages

Amazon Ads

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X / Twitter Ads

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Snapchat Ads

LinkedIn Pages

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Spotify Ads

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Mailchimp

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ActiveCampaign