Google Analytics 4 to Databricks: 2 Easy Steps to Replicate Data

By: Published: September 13, 2022

Google Analytics 4 to Databricks_FI

Since Google Analytics 4 provides native integration with Google BigQuery, tooling support outside the GCP environment is lacking. Because Google BigQuery controls slot allocation for each query made, it lacks autoscaling capabilities essential for scenarios when data starts increasing massively.

This is where you can opt for a platform that puts the autoscaling feature at your disposal. On replicating data from Google Analytics 4 to Databricks, you will have a single source of truth for your traffic and engagement data. On top of Databricks, you can replicate data from multiple platforms, not just Google Analytics 4, to supercharge the decision-making process, perform advanced analytics, and build machine learning models.

This article explains, in 3-easy-steps, how to connect Google Analytics 4 to Databricks using Hevo’s Automated Data Pipeline Platform.

Table of Contents

Replicate data from Google Analytics 4 to Databricks Using Hevo

With Hevo, the process of replicating data from Google Analytics 4 to Databricks can be a seamless one.

Step 1: Configure Google Analytics 4 as your Source

Configure Google Analytics 4 as the source.

Configure Google Analytics 4 as a source for replicating Google Analytics 4 to Databricks
Image Source

Note: You can select from the “Historical Sync Duration” according to your requirements where the default duration is 6 months. You can enable the “Pivot Report” option if you want to create an aggregated report based on the dimensions and metrics selected.

Step 2: Configure Databricks as your Destination

Now, you need to configure Databricks as the destination.

Configure Databricks as a destination for replicating Google Analytics 4 to Databricks
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All Done to Setup Your ETL Pipeline

After implementing the above 2 steps, Hevo will replicate your data from Google Analytics 4 to Databricks based on your configurations.

Hevo’s data pipeline will automatically replicate new and updated data from Google Analytics 4 to Databricks every 1 hour (by default). However, you can also adjust the data replication frequency as per your requirements.

Data Replication Frequency

Default Pipeline FrequencyMinimum Pipeline FrequencyMaximum Pipeline FrequencyCustom Frequency Range (Hrs)
1 Hr15 Mins12 Hrs1-12

You can also visit the official documentation of Hevo for Google Analytics 4 as a source and Databricks as a destination to have in-depth knowledge about the process.

Replicating Data From Google Analytics 4 Data to Databricks is Advantageous — here’s why

  • Multicloud Integration: Google Analytics 4 native integration with BigQuery allows you to move your raw data to Google BigQuery without cost, but the data is only restricted to Google Cloud. Now, your Google Analytics 4 data in Databricks can be integrated and moved freely across multiple cloud services, i.e., AWS, Azure, and Google Cloud. You don’t need to reinvent the integrations separately for every cloud platform. 
  • Support for Autoscaling: Due to data scaling limitations associated with BigQuery integration, Databricks takes an edge. With increasing workload demand, query processing time also increases. Since BigQuery has complete control over when to allocate slots for each query, the user can’t adjust the compute time for faster query execution. Databricks supports autoscaling, in which the clusters are resized automatically based on workload demand.
  • Build Machine Learning Models: Google Analytics 4 uses machine learning capabilities with little to no customizability to forecast marketing initiatives’ success or failure. Contrary to this, with your Google Analytics 4 raw data in Databricks, you would get full support of a suite of ML-powered predictive analytics tools such as Apache Spark, Python, Scala, ML flow, Keras, scikit-learn, and many more. Stepping up your data analytics capabilities to the next level is the name of the game.
  • Get more insights into Customer Journeys: With your Google Analytics 4 data in Databricks, you can integrate this data with other data sources to get a holistic view of KPIs in customer journeys. You can add parameters such as advertising revenues, data from different CRMs, and many more.
  • Get a Clear View of the Attribution Model: With your Google Analytics 4 data in Databricks, you can measure the effectiveness of different customer touchpoints and the credits associated with every touchpoint. You can evaluate and customize the attribution model based on your selected factors.

Why Use Hevo?

If yours anything like the 1000+ data-driven companies that use Hevo, more than 70% of the business apps you use are SaaS applications. Integrating the data from these sources in a timely way is crucial to fuel analytics and the decisions that are taken from it. But given how fast API endpoints etc can change, creating and managing these pipelines can be a soul-sucking exercise.

Hevo’s no-code data pipeline platform lets you connect over 150+ sources in a matter of minutes to deliver data in near real-time to your warehouse. What’s more, the in-built transformation capabilities and the intuitive UI means even non-engineers can set up pipelines and achieve analytics-ready data in minutes. 

All of this combined with transparent pricing and 24×7 support makes us the most loved data pipeline software in terms of user reviews.

Take our 14-day free trial to experience a better way to manage data pipelines.

Get started for Free with Hevo!

Here’s what makes Hevo stands out from the crowd:

  • Fully Managed: You don’t need to dedicate any time to building your pipelines. With Hevo’s dashboard, you can monitor all the processes in your pipeline, thus giving you complete control over it.
  • Data Transformation: Hevo provides a simple interface to cleanse, modify and transform your data through drag-and-drop features and Python scripts. It can accommodate multiple use cases with its pre-load and post-load transformation capabilities.
  • Faster Insight Generation: Hevo offers near real-time data replication, so you have access to real-time insight generation and faster decision-making. 
  • Schema Management: With Hevo’s auto schema mapping feature, all your mappings will be automatically detected and managed to the destination schema.
  • Scalable Infrastructure: With the increase in the number of sources and volume of data, Hevo can automatically scale horizontally, handling millions of records per minute with minimal latency.
  • Transparent pricing: You can select your pricing plan based on your requirements. Different plans are clearly put together on its website, along with all the features it supports. You can also adjust your credit limits and spend notifications for any data flow increases.
  • Live Support: The support team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.

Winding up With Final Words

This article has provided a simple solution for replicating data from Google Analytics 4 to Databricks. Following that, we explored some advantages of integrating the above-mentioned tools.

The clusters’ size in Databricks will automatically resize based on workflow demand. As a result, your query processing time is now optimized with support from ML-powered predictive analytics tools.

Google Analytics 4 to Databricks integration will complement your decision-making capabilities with the much-needed finesse.

Hevo offers a 14-day free trial. Check out this video to know how Hevo works.

Hevo, being fully automated along with 150+ plug-and-play sources, can accommodate a variety of your use cases.

Former Research Analyst, Hevo Data

Manisha is a data analyst with experience in diverse data tools like Snowflake, Google BigQuery, SQL, and Looker. She has written more than 100 articles on diverse topics related to data industry.

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