Web design, search engine optimisation and Development

UA to GA 4 : Safeguarding UA Historical Data and Embracing Google Analytics 4

UA to GA 4 : Safeguarding UA Historical Data and Embracing Google Analytics 4

July 2023, the digital landscape experiences a significant change with the cessation of data collection by Universal
Analytics. The baton has been passed to the new and promising Google Analytics 4, which takes the center stage as
the successor. As this transition occurs, many users find themselves pondering a crucial question: Can the
historical data accumulated in Google Analytics Universal be seamlessly transferred to Google Analytics 4?

Unfortunately, the answer to this burning question is not what everybody wants to hear. Directly transferring data
between the two interfaces is not an option. However, there’s no need to fret, as a solution exists to preserve your
invaluable data outside the Google Analytics interface.

In this article, we will guide you through a process that allows you to safeguard your data, ensuring it remains
accessible for future analysis and usage. By adopting this approach, you can smoothly navigate the shift to Google
Analytics 4 while retaining access to your historical insights. Embrace the change and empower yourself to make the
most of Google Analytics’ new features while cherishing the data that has been the foundation of your digital
journey so far.

Understanding the Incompatibility: Differences Between Universal Analytics and Google Analytics 4 Data Models

As Google Analytics bids farewell to Universal Analytics and embraces the innovative Google Analytics 4, users are
faced with the challenge of data migration. The reason behind the impossibility of direct data transfer lies in the
fundamental differences between the data models of the two systems.

Universal Analytics relies on a session data model, whereas Google Analytics 4 operates on an event model. This
difference in data structure makes it intricate to seamlessly transfer historical data from one system to another.
While some settings for users, events, goals, conversions, and audiences can be transferred, the core data structure
remains incompatible.

Furthermore, dimensions and metrics are defined and calculated differently in the two systems, adding another layer
of complexity to the data migration process. The dissimilarity in data export schemas between Universal Analytics
and Google Analytics 4 further highlights the contrasting nature of their data models.

In Universal Analytics data exports, each line represents a session, and interactions within that session are listed
on individual lines. Conversely, in Google Analytics 4 exports, each line represents an individual event,
encapsulating a specific interaction.

Despite the challenges of data migration, users can still make the most of Google Analytics 4’s advanced features
and embrace the new data model while preserving their historical data outside the platform. Understanding the
incompatibility is key to effectively managing this transition and unlocking the full potential of Google Analytics
4 in the ever-evolving digital landscape.

Embracing Google BigQuery: Mitigating the Impact of Universal Analytics Shutdown on Reports

With the shutdown of Universal Analytics and the switch to Google Analytics 4, there are significant implications
for the reports that rely on Universal Analytics data. As the Universal Analytics API stops updating with new hits,
the reports dependent on this data source will no longer receive real-time updates, potentially leading to gaps in
data and incomplete insights.

To circumvent this issue and ensure the continuity of data-driven decision-making, users can take advantage of
Google BigQuery. By uploading their Google Universal Analytics data to Google BigQuery, they can preserve and
maintain access to their historical data outside of the Universal Analytics interface. This proactive measure allows
businesses and website owners to continue running their reports using the accumulated data, ensuring a seamless
transition to Google Analytics 4 without losing valuable insights.

By harnessing the power of Google BigQuery, users can not only protect their historical data but also explore new
analytical opportunities and leverage the advanced capabilities of Google Analytics 4. Embracing this solution
equips businesses with the tools they need to make informed decisions and stay ahead in an ever-evolving digital

Exploring Ways to Preserve Data from Universal Analytics Property

As the transition from Universal Analytics to Google Analytics 4 takes center stage, the need to safeguard
historical data becomes crucial for users seeking valuable insights. Fortunately, Google Analytics provides several
efficient methods to export data from your Universal Analytics property, ensuring data continuity and accessibility.

One approach is to manually export individual reports in various formats, such as CSV, ТСВ, TSV for Excel, Excel
(XLSX), Google Sheets, and PDF. This enables users to extract specific data sets tailored to their unique

For more advanced users, Google Analytics Dev Tools like the Query Explorer (API) offer programmable data export,
granting greater flexibility and control during the extraction process.

Another effective solution is to utilize the Google Analytics Spreadsheet Add-on (API), simplifying data export to
spreadsheets and streamlining data management.

For Google Analytics 360 customers, the BigQuery Export feature proves to be a potent solution, facilitating
seamless integration with Google BigQuery and providing a comprehensive data warehousing option for large-scale data
analysis and exploration.

While these existing export options offer robust means to preserve Universal Analytics data, Google’s ongoing
support includes exploring potential enhancements for exporting historical data. The future may bring even more
streamlined and versatile methods for users to safeguard their valuable data, ensuring a smooth transition to
leverage the advanced capabilities of Google Analytics 4.

Wrapping up,

As Universal Analytics makes way for Google Analytics 4, users face the challenge of data migration due to the
differences in data models between the two platforms. Directly transferring historical data is not feasible, but
users can rest assured that their data can be preserved and accessed outside the Google Analytics interface.
Embracing Google BigQuery offers a proactive solution to mitigate the impact of Universal Analytics shutdown on
reports, allowing users to continue making data-driven decisions. Additionally, Google Analytics provides various
export options for Universal Analytics data, ensuring data continuity and accessibility. While the transition may
present its challenges, Google’s ongoing commitment to improving data export options promises a brighter future for
users seeking to safeguard their valuable data while unlocking the full potential of Google Analytics 4 in the
ever-evolving digital landscape.

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