GA3 Historical Data Migration

Migrate all your historical data from GA3 to Cloud Platforms including AWS, Big Query, and Azure. With the help of our Google Analytics Certified specialists, begin your GA3 Data Migration right away.Why is Historical Data Migration required

Data Sampling

GA3 Sunset

Universal Analytics will stop collecting data starting from 1st July 2023.

Data Retention

Historical Data Loss

Prevent data loss by migrating GA3 historical data.

BigQuery Export


Measuring performance and progress over time.



Leverage historical audience in GA4 for remarketing & ML

+ more

DWAO will make your Historical Data Migration Successful

Download, Export all historical data from UA to your desired cloud platform and then connect it with any reporting platform of your choice.

Frequently Asked Questions

Frequently Asked Questions

When should I start the UA data migration?

It’s high time to migrate from Universal Analytics to the cloud platform of your choice as July 1st is about to come and Google will start restricting UA for data collection. After the termination date (July 1, 2023) you will only have access to historical reports for six months before completely losing access to the data

How much time will it take to migrate UA data to Cloud platforms?

DWAO can migrate historical data in a minimum of two weeks or a maximum of four weeks, but it also depends on the volume of your data.

How can I transfer my Universal Data to GA4?

There is no standard way to migrate your Universal data to GA4, as both platforms are based on different data collection models. However, we can assist you with dashboards that provide data trends in a single report!

Can I merge GA3 & GA4 Data in a single report?

Yes, you can merge and consolidate the data from both GA3 & GA4 platforms post-migration for applicable metrics and dimensions.

Can I create audiences based on GA3 historical data & GA4?

Yes, we have a unique approach that will help you to create audiences based on your historical data which is available in your GA3 Platform.

There are certain limitations and prerequisites to it*.

Why should I transfer my historical old data?

Data is required for decision making hence there is no question why you should transfer your data from universal analytics. Historical data will assist with campaign performance analysis, historical behaviour analysis, enhanced reporting etc.

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Benefits of Historical Data Migration from Universal Analytics

GA4 360 Account Activation

Trends Analysis

This will help you with trends analysis with respect to any metrics e.g. user, sessions, pageviews, bounce rate etc.

GA4 360 Support

Performance Benchmarking

You can do the performance benchmarking with respect to CTR, Cost, CPA etc

GA4 360 Managed Services

Predictive Analysis

Historical data can be used for creating machine learning models and future forecastingn. Finally it will help you with valuable insights and help you your organization to make important decisions.

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How Will DWAO help you with GA4 360

How Will DWAO help you with Historical Data Export or Download


1.Universal Analytics Data Migration

we discuss the old data migration requirement with different stakeholders in your team. Create the strategy and then plan the migration approach to ensure you can drive maximum juice of out it.

2.Audience Migrationn

GA4 offers audience definition migration, but not the actual audience migration from GA3 to GA4. We have a unique solution that can assist you in migrating your historical audiences to GA4. This will enable you to optimize your media campaigns in the same manner as you were handling them in GA3.

3.GA3 and GA4 Data Consolidation

We can assist you in consolidating historical data that you extract from Universal Analytics and merge with GA4. Since both platforms operate on different data collection models, DWAO can help you merge the key data points and provide you with consolidated reports.


After the data is migrated to the cloud, we will assist you with generating reports and insights, and create different dashboards using tools such as Data Studio, Tableau, Excel, Google Sheets, and others.

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