Google Analytics is the most popular web analytics service on the market, used to gather crucial information on website events: web traffic, purchases, signups, and other aspects of browser/customer behavior. However, the vast amount of data that Analytics provides makes it necessary for many users to search for ways to more deeply analyze the information found within the platform. Enter Snowflake, a platform designed from the ground up to be a cloud-based data warehouse. You can read more about Snowflake here. For many users of Analytics, Snowflake is the ideal solution for their data analysis needs, and in this article, we will walk you through the process of moving your data from Google Analytics to Snowflake.
Introduction to Google Analytics
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Google Analytics (GA) is a Web Analytics service that offers Statistics and basic Analytical tools for your Search Engine Optimization (SEO) and Marketing needs. It’s free and part of Google’s Marketing Platform, so anyone with a Google account may take advantage of it.
Google Analytics is used to monitor website performance and gather visitor data. It can help organizations identify the most popular sources of user traffic, measure the success of their Marketing Campaigns and initiatives, track objective completion, discover patterns and trends in user engagement, and obtain other visitor information, such as demographics. To optimize Marketing Campaigns, increase website traffic, and better retain visitors, small and medium-sized retail websites commonly leverage Google Analytics.
Here are the key features of Google Analytics:
- Conversion Tracking: Conversion points (such as a contact form submission, e-commerce sale, or phone call) can be tracked in Google Analytics once they have been recognized on your website. You’ll be able to observe when someone converted, the traffic source that referred them, and much more.
- Third-Party Referrals: A list of third-party websites that sent you traffic will be available. That way you’ll know which sites are worth spending more time on, as well as if any new sites have started linking to yours.
- Custom Dashboards: You can create semi-custom Dashboards for your analytics with Google Analytics. You can add Web Traffic, Conversions, and Keyword Referrals to your dashboard if they’re essential to you. To share your reports, you can export your dashboard into PDF or CSV format.
- Traffic Reporting: Google Analytics is essentially a traffic reporter. How many people visit your site each day will be revealed by the service’s statistics. You may also keep track of patterns over time, which can help you make better decisions about online Marketing.
Introduction to Snowflake
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Snowflake is a cloud data warehouse that came out in 2015. It is primarily available on AWS and Azure. Snowflake is similar to BigQuery in that it stores data separately from where it does its compute. It stores the actual data of your tables in S3 and then it can provision any number of compute nodes to process that data.
In contrast, Snowflake offers instant access to unlimited resources (compute and storage) on-demand.
Snowflake Benefits:
- Snowflake is specifically optimized for analytics workloads. It’s therefore ideal for businesses dealing with very complex data sets.
- Snowflake offers better performance both in terms of storage capacity and query performance.
- Snowflake also offers better security compared to an on-prem data warehouse. This is because cloud data warehouses are required to meet stringent security requirements.
- Migrating your data to the cloud is also cost-effective since there is no huge initial outlay and you don’t have to maintain physical infrastructure.
This article provides an overview of both the above approaches. This will allow you to assess the pros and cons of both and choose the route that suits your use case best
Understanding the Methods to Connect Google Analytics to Snowflake
Here are the methods you can use to establish a connection from Google Analytics to Snowflake:
Method 1: Using Custom ETL Scripts to Move Data from Google Analytics to Snowflake
Here are the steps you can use to set up a connection from Google Analytics to Snowflake using Custom ETL Scripts:
Step 1: Accessing Data on Google Analytics
The first step in moving your data is to access it, which can be done using the Google Analytics Reporting API. Using this API, you can create reports and dashboards, both for use in your Analytics account as well as in other applications, such as Snowflake. However, when using the Reporting API, it is important to remember that only those with a paid Analytics 360 subscription will be able to utilize all the features of the API, such as viewing event-level data, while users of the free version of Analytics can only create reports using less targeted aggregate data.
Step 2: Transforming Google Analytics Data
Before transferring data to Snowflake, the user must define a complete and well-ordered schema for all included data. In some cases, such as with JSON or XML data types, data does not need a schema in order to be transferred directly to Snowflake. However, many data types cannot be moved quite so readily, and if you are dealing with (for example) Microsoft SQL server data, more work is required on the part of the user to ensure that the data is compatible with Snowflake.
Google Analytics reports are conveniently expressed in the manner of a spreadsheet, which maps well to the similarly tabular data structures of Snowflake. On the other hand, it is important to remember that these reports are samples of primary data, and as such, may contain different values during separate report instances, even over the same time period sampled.
Because Analytics reports and Snowflake data profiles are so similarly structured, a common technique is to map each key embedded in a Report API endpoint response to a mirrored column on the Snowflake data table, thereby ensuring a proper conversion of necessary data types. Because data conversion is not automatic, it is incumbent on the user to revise data tables to keep up with any changes in primary data types.
Step 3: Transferring Data from Google Analytics to Snowflake
There are three primary ways of transferring your data to Snowflake:
- COPY INTO – The COPY INTO command is perhaps the most common technique for data transferral, whereby data files (stored either locally or in a storage solution like Amazon S3 buckets) are copied into a data warehouse.
- PUT – The PUT command may also be used, which allows the user to stage files prior to the execution of the COPY INTO command.
- Upload – Data files can be uploaded into a service such as the previously mentioned Amazon S3, allowing for direct access of these files by Snowflake.
Step 4: Maintaining Data on Snowflake
Maintaining an accurate database on Snowflake is a never-ending battle; with every update to Google Analytics, older data on Snowflake must be analyzed and updated to ensure the integrity of the overarching data tables. This task is made somewhat easier by creating UPDATE statements in Snowflake, but you must also take care to identify and delete any duplicate records that appear in the database.
Overall, maintenance of your newly-created Snowflake database can be a time-consuming project, which is all the more reason to look for time-saving solutions such as Hevo.
Limitations of Using Custom ETL Scripts to Connect Google Analytics to Snowflake
Although there are other methods of integrating data from Google Analytics to Snowflake, those not using Hevo must be prepared to deal with a number of limitations:
- Heavy Engineering Bandwidth: Building, testing, deploying, and maintaining the infrastructure necessary for proper data transfer requires a great deal of effort on the end user’s part.
- Not Automatic: Each time a change is made in Google Analytics, time must be taken to manually alter the code to ensure data integrity.
- Not Real-time: The steps as set out in this article must be performed every single time data is moved from Analytics to Snowflake. For most users, who will be moving data on a regular basis, following these steps every time will be a cumbersome, time-consuming ordeal.
- Possibility of Irretrievable Data Loss: If at any point during this process an error occurs say, something changes in Google Analytics API or on Snowflake, serious data corruption and loss can result.
Method 2: Using Hevo Data to Move Data from Google Analytics to Snowflake
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Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
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Hevo takes care of all your data preprocessing to set up a connection from Google Analytics to Snowflake and lets you focus on key business activities and draw a much powerful insight on how to generate more leads, retain customers, and take your business to new heights of profitability. It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination.
Hevo being an official Snowflake partner, can connect Google Analytics to Snowflake in 2 simple steps:
- Step 1: Connect Hevo with Google Analytics 4 and all your data sources by simply logging in with your credentials.
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- Step 2: Configure the Snowflake destination by providing the details like Destination Name, Account Name, Account Region, Database User, Database Password, Database Schema, and Database Name.
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Hevo will now take care of all the heavy-weight lifting to move data from Google Analytics to Snowflake. Here are some of the benefits of Hevo:
- Reduced Time to Implementation: With a few clicks of a mouse, users can swiftly move their data from source to destination. This will drastically reduce time to insight and help your business make key decisions faster.
- End to End Management: The burden of overseeing the inessential minutiae of data migration is removed from the user, freeing them to make more efficient use of their time.
- A Robust System for Alerts and Notifications: Hevo offers users a wide array of tools to ensure that changes and errors are detected and that the user is notified as to their presence.
- Complete, Consistent Data Transfer: Whereas some data migration solutions can lead to the loss of data as errors appear, Hevo uses a proprietary staging mechanism to quarantine problematic data fields so that the user can fix errors on a case-to-case basis and move this data.
- Comprehensive Scalability: With Hevo, it is no problem to incorporate new data sets, regardless of file size. In addition to Google Analytics, Hevo is also able to interface with a number of other analytics, marketing, and cloud applications; Hevo aims to be the one-source solution for all your data transfer needs.
- 24/7 Support: Hevo provides a team of product experts, ready to assist 24 hours a day, 7 days a week.
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Conclusion
For users who seek a more in-depth understanding of their web traffic, moving data from Google Analytics to their Snowflake data warehouse becomes an important feat.
However, sifting through this can be an arduous and time-intensive process, a process that a tool like Hevo can streamline immensely, with no effort needed from the user’s end. Furthermore, Hevo is compatible with a 100+ data sources, including 40+ Free Sources like Google Analytics allowing the user to interface with databases, cloud storage solutions, and more.
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Nathaniel is a freelance writer having a passion towards writing about the data industry who loves creating informative content on data analytics, machine learning, AI, big data, and business intelligence topics.