Google Analytics 4 will replace Universal Analytics on 1st July 2023. For the customers of Google Analytics 360, which is a paid version of GA, the transitional period has been extended to 1st July 2024. However, irrespective of the GA version you use, it’s only a matter of time for the reports to be upgraded to the new data model. Today we are going to discuss why it is good to link GA4 with BigQuery.
Universal Analytics with Google Analytics 4 – Why it is good to connect these two platforms now
Google Analytics Universal (UA) and Google Analytics 4 (GA4) are two different versions of the online Google Analytics Platform. They both use different tracking codes and data models. However, it is possible to link UA with GA4.
We recommend connecting Google Analytics 4 (GA4) to the existing Google Analytics (Universal Analytics) as soon as possible. It will enable to collect data simultaneously on two platforms and prevent the data gaps. Once these two services are connected, the data will be sent both to Universal Analytics and GA4. It is thereby important to remember to update all the integrations or reporting tools which are based on the Universal Analytics data.
Connecting Google BigQuery to Google Analytics 4 (GA4) – the advantages
Connecting Google Analytics 4 (GA4) to Google BigQuery gives a powerful solution for analysing and processing large quantities of data. There are several reasons why to connect Google BigQuery with Google Analytics 4 (GA4):
- Possibility to store and analyze large quantities of data. GA4 GA generates a lot of data, and BigQuery is a cloud-based data warehouse. It allows to store and analyze large databases using SQL queries.
- Customized analyses and reports: BigQuery allows to perform customized analyses and reports for GA4 data. By using SQL queries, you can extract accurate data and create customized reports.
- Data integration: BigQuery integrates well with other data sources. It enables blending GA4 data with the data from other sources, such as CRM systems, for example Salesforce and marketing automation platforms, among others. Such integration may give you a clear picture of the customer behaviours and help make more informed business decisions.
- Machine Learning: BigQuery provides a wide spectrum of advanced analytical functions, such as Machine Learning and predictive modelling. By connecting GA4 data to other data sources you can create more advanced models which will help you predict future behaviours and identify new opportunities.
- Profitability: BigQuery offers a flexible pricing model. Prices are determined based on single queries, so you pay only for the actual data storage and processing.
Google Analytics 4 (GA4) as the data source for the ETL process
Google Analytics 4 (GA4) can be used as the source of data for the ETL (Extract, Transform, Load). Below are the example applications of GA4 in the ETL process:
- Extract the information that is important for you. GA4 data can be extracted from the Google Analytics API by using SQL or a programming language such as Python. Such data can be regularly downloaded to ensure the ETL process has access to the most up-to-date data.
- Transformation: After the data is extracted, you can transform it to match the format and structure required by the target system. This may involve filtering out any unnecessary data, aggregating the data at various levels of detail, and mapping the data to appropriate fields in the target system.
- Loading data: once your data is transformed, you can feed it to the target system – for example, a data warehouse or a tool for business analysis. The target system can be configured to accept the transformed data in the required format.
BigQuery- how to connect with GA4
BigQuery is a cloud-based data warehouse that allows to store and analyze large datasets using SQL queries. It is a component of the Google Cloud Platform, and it integrates well with other Google products, such as Google Analytics.
In order to use GA4 data in BigQuery, you need to connect your GA4 services to BigQuery. Once it is done, GA4 will automatically start exporting the data to BigQuery. Next, you can use BigQuery to analyze the data using SQL queries or to connect it to other tools such as Power BI, Tableau ,or Data Studio.
GA4 Data in BigQuery is broken down into several tables – each table contains several types of data such as user details, events and parameters. You can send queries to these tables to get insights about user behaviours, analyze paths and other data.
Do you need help to connect GA4 with BigQuery?
When connecting GA4 with BigQuery, it is important to find a consultancy company such as NDLS, whose team consists of consultants, who:
Have experience in working with BigQuery and cloud-based solutions for data warehouses. They have a deep understanding of the data architecture and ETL processes and also have experience in SQL and other tools for data analysis.
They can clearly and effectively communicate with your team. Our specialists can explain complex concepts easily and comprehensibly and work effectively with your team in order to satisfy your needs as regards the data.
They can meet the requirements of your budget and schedule.
They have experience in working with sensitive data and can ensure data security and legal compliance.
Contact NewDataLabs, and we will help you connect Google Analytics4 with BigQuery in your company.
