Google Analytics 360 to Snowflake Integration: 2 Easy Methods

• July 15th, 2022

Google Analytics 360 to Snowflake FI

Google provides a web analytics tool, Google Analytics, that offers statistics and standard analytics tools for online marketers. It provides several services like Google Tags Manager, Google Optimize, and Google Ad Manager for free. However, as enterprises expand, these free tools, especially Google Analytics, are insufficient to provide all the insights required for analysis. Google Analytics 360 is the premium version of Google Analytics that allows you to draw more robust and detailed insights from your website data.

It comprises the 360 versions of previously available tools like Attribution, Google Optimize, Audience Center, Data Studio, Tag Manager, and Analytics. These tools let you track your customers’ actions and engagement. But, to draw in-depth insights from your website data, you can centralize it by storing it in cloud data warehouses like Snowflake. 

This article explains two methods to connect Google Analytics 360 to Snowflake and the limitations of doing so.

Table of Contents

Prerequisites

  • Basic understanding of Google Analytics and integration.

What is Google Analytics 360?

Google Analytics 360 to Snowflake: logo
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Google Analytics 360 is a part of Google’s Analytics 360 Suite, an integrated solution to enhance marketing and customer experience. It is one of the most popular platforms that track user engagement and enables you to get meaningful insights. Analytics 360 provides enterprise-level tools for data from all touchpoints to understand user behavior better. With Analytics 360, you can also avail a more comprehensive native onboarding list with additions like DoubleClick Bid Manager, DoubleClick Campaign Manager, and DoubleClick Search. 

Key Features of Google Analytics 360

GA360 enables you to gather extensive data and get complete insights into your site’s performance and marketing campaigns with the following benefits and features:

  • Enhanced Data Freshness and HIT LIMIT: GA360 allows you to start from 500M hits/month compared to only 100M hits for the free version. Furthermore, it enables data processing in just 10-15 minutes (usually) and may take up to 4 hours based on the dataset. This is a significant advantage over the free version, which could take up to 24 hours to do.
  • More Integrations: Google Analytics 360 allows you to integrate with BigQuery for super-fast queries of large data sets. You can now easily export all sessions, hit data, and then run any custom queries required. Other than that, GA360 can also integrate with Salesforce Sales Cloud and Google Cloud.
  • Custom Funnels: Google Analytics 360 allows you to make Custom Funnels to visualize better how users interact with your website. You can then act based on this information to improve your website’s functionality and reduce inefficiencies.
  • Advanced Analysis: This feature allows you to have impactful audience discovery and comparison tools. Drag and drop dimensions and required metrics onto your analysis canvas and export your findings to Google Analytics. You can then compare and contrast different analysis techniques and switch between them accordingly. 
  • Certified Partner: Google Analytics 360 works as a certified business accomplice to ensure that your enterprise gets the most out of your subscription to Google Marketing Platform. You can always get in touch with their top-of-the-line administrators and get guidance for a market-driven aptitude. 

What is Snowflake?

Google Analytics 360 to Snowflake: snowflake logo
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Snowflake is one of the most popular data platforms which operates as a cloud data warehouse to support multi-cloud infrastructure environments. Developed in 2012, the Snowflake platform is a fully managed SaaS (software-as-a-service) that allows you to store and compute while scaling independently. The cloud platform offers many unique features like on-the-fly scalable compute, separation of storage and compute (like in BIgQuery), data cloning, data sharing, and third-part tools support.

Snowflake comprises three main components, Cloud Services, Query Processing, and Database Storage.

  • Cloud Services: Snowflake utilizes ANSI SQL for data management and optimization. These services cover infrastructure management, query parsing, authentication, and metadata management. The platform also maintains PCI DSS and HIPAA certifications for security and data encryption. 
  • Query Processing: Snowflake’s compute layer consists of virtual cloud data warehouses where you can analyze data via requests. These virtual warehouses are independent and do not compete for resources or affect each other’s performance.
  • Database Storage: A database is where an enterprise uploads its structured and semi-structured data for processing and analysis. Snowflake automatically caters to all parts of storing and retrieving, including organization, metadata, structuring, file sizing, compression, and statistics.

Key Features of Snowflake

Snowflake has the edge over other cloud data platforms due to a few distinctive and noteworthy features. These include:

  • Cloud Agnostic Solution: Snowflake is a cloud-agnostic solution. It is available on Google Cloud Platform, Amazon Web Services, and Microsoft Azure. It enables you to have similar deployment options and the same end-user experience while leveraging Snowflake into your current cloud architecture.
  • Workload Separation: Traditional warehouses have a few concurrency issues, wherein users and processes compete for resources. With Snowflake’s multi-cluster architecture, this issue is completely solved. It separates workloads to be executed via its compute clusters (virtual warehouse). 
  • Near-Zero Administration: Snowflake does not require any prior software or hardware installation. It is generally delivered as a warehouse service to manage data without much involvement from IT teams or database administrators (DBA). 
  • Compatible with Storing Semi-Structured Data: Snowflake’s architecture enables you to store structured and semi-structured data at the same destination using the ‘VARIANT’ schema on the read data type. Then, it automatically parses data to extract attributes and stores it in columns. Thus, it eliminates the necessity of data extraction pipelines. 

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Methods to Connect Google Analytics 360 to Snowflake

Google Analytics 360 provides many actionable and meaningful insights related to your website, but they are still limited by Google’s offerings. If you wish to draw more insights and perform in-depth analysis, you should connect Google Analytics 360 to Snowflake. 

Given below are two methods to connect Google Analytics 360 to Snowflake:

Method 1: Connect Google Analytics 360 to Snowflake using Hevo

Google Analytics 360 to Snowflake: hevo banner
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Hevo provides Snowflake as a Destination for loading/transferring data from any Source system, which also includes Google Analytics 360. You can refer to Hevo’s documentation for Permissions, User Authentication, and Prerequisites for Snowflake as a destination here for Google Analytics 360 to Snowflake Connector. 

Configure Google Analytics 360 as a Source

Configure Google Analytics 360 as the Source in your Pipeline to connect Google Analytics 360 to Snowflake by following the steps below:

  • Step 1: In the Asset Palette, select PIPELINES.
  • Step 2: In the Pipelines List View, click + CREATE.
  • Step 3: Select Google Analytics 360 on the Select Source Type page for Google Analytics 360 to Snowflake Migration.
  • Step 4: Click + ADD BIGQUERY ACCOUNT on the page Configure your Bigquery account linked to Google Analytics 360.
  • Step 5: To give Hevo read access to your analytics data, go to your linked Google account and select BigQuery DataViewer privilege. Then click Allow for Google Analytics 360 to Snowflake Integration.
Google Analytics 360 to Snowflake: configure source
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  • Step 6: Set the following parameters on the Configure your Google Analytics 360 Source page to connect Google Analytics 360 to Snowflake:
    • Pipeline Name: A name for your Pipeline that is unique and does not exceed 255 characters.
    • Project ID: The BigQuery project ID that is linked to your GA 360 account.
    • Dataset ID: The name of the Google Analytics 360 dataset that contains your data. The dataset ID becomes available for selection in the drop-down after your GA 360 account is linked to your BigQuery project. Contact Hevo Support if you don’t see your dataset ID listed in the drop-down.
    • Historical Sync Duration: The amount of time that previous data must be ingested. All Available Data is the default value.
  • Step 7: TEST & CONTINUE is the button to click.
  • Step 8: Set up the Destination.

Configure Snowflake as a Destination

To set up Snowflake as a destination in Hevo for Google Analytics 360 to Snowflake Connection, follow these steps:

  • Step 1: In the Asset Palette, select DESTINATIONS.
  • Step 2: In the Destinations List View, click + CREATE for Google Analytics 360 to Snowflake Integration.
  • Step 3: Select Snowflake from the Add Destination page.
  • Step 4: Set the following parameters on the Configure your Snowflake Destination page for Google Analytics 360 to Snowflake Connection:
Google Analytics 360 to Snowflake: config destination
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  • Destination Name: Give your destination a unique name.
  • Database Cluster Identifier: The IP address or DNS of the Snowflake host is used as the database cluster identifier.
  • Database Port: The port on which your Snowflake server listens for connections is the database port. 5439 is the default value.
  • Database User: In the Snowflake database, a user with a non-administrative position.
  • Database Password: The user’s password.
  • Database Name: The name of the destination database into which the data will be loaded.
  • Database Schema: The Destination database schema’s name. The default setting is public.
  • Step 5: To test connectivity with the Snowflake warehouse, click Test Connection to complete Google Analytics 360 to Snowflake Integration.
  • Step 6: When the test is complete, select SAVE DESTINATION.

With this, you have successfully connected Google Analytics 360 to Snowflake.

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  • In-built Transformations: Format your data on the fly with Hevo’s preload transformations using either the drag-and-drop interface, or our nifty python interface. Generate analysis-ready data in your warehouse using Hevo’s Postload Transformation.
  • Near Real-Time Replication: Get access to near real-time replication for all database sources with log based replication. For SaaS applications, near real time replication is subject to API limits.   
  • Auto-Schema Management: Correcting improper schema after the data is loaded into your warehouse is challenging. Hevo automatically maps source schema with destination warehouse so that you don’t face the pain of schema errors.
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Method 2: Manually Connect Google Analytics 360 to Snowflake

To manually connect Google Analytics 360 to Snowflake follow the below steps:

Exporting Data from Google Analytics 360

 Follow these steps to export data from Google Analytics 360 for Google Analytics 360 to Snowflake Connection:

  • Step 1: Open the desired report to export.
  • Step 2: Click on Export.
  • Step 3: Choose the format you want to export the file, such as TSV, CSV, Excel, PDF, and more.
  • Step 4: Your report is converted into the selected format and is available in the download directory. 

Importing Data into Snowflake

You can follow the steps given below to load data in Snowflake to perform Google Analytics 360 to Snowflake Integration:

  • Step 1: Populate Data into the Warehouse.
    • Click on Data > Databases (on Snowflake homepage).
    • To view the content, click on the database link.
    • Create a table by either ‘choosing a row’ to load it or ‘choosing the table name’.
    • Once you select an option, the loading wizard appears to populate the data into the table.
  • Step 2: Select Preferred Warehouse.
    • Using the drop-down menu, select the warehouse.  
    • Proceed by clicking on Next.
  • Step 3: Loading Files.
    • Click on Load files from your computer > Select Files.
    • Once you choose one or more data files, click ‘Open’.
    • Press the ‘Next’ key once you are done.
  • Step 4: Selecting a File Format.
    • If the file format already exists:
      • Choose the preexisting format.
      • Click Next.
    • For a new File Format:
      • Click the plus (+) sign from the drop-down list.
      • Fill in the fields that appear on your screen based on the format of your data files.
      • Click on Finish.
      • Select the new file format you want from the drop-down menu.
      • Click Next.
  • Step 5: Setting Up Load Options.
    • Specify an action by Snowflake in case the data files have anomalies.
    • From the menu, select Load. Snowflake will use the warehouse of your choice to import data in your chosen table.
    • Click OK once you are done. The loading wizard completes the loading data. 

You have successfully connected Google Analytics 360 to Snowflake manually.

Limitations of Manually Connecting Google Analytics 360 to Snowflake

Manual integration of Google Analytics 360 to Snowflake may seem convenient, given the steps, but there are some limitations. Google Analytics 360 Data migration takes a lot of time. You must repeat the steps whenever you wish to transfer data from GA360 to Snowflake. The process also becomes a little more complex as it cannot be done in real-time.

There is also a risk of data security while exporting it from Google Analytics 360 to Snowflake. To avoid such challenges, you can always get assistance from third-party ETL providers like Hevo. You have to choose the source and the sink; Hevo will do the rest. 

Conclusion

In this article, you learned the benefits of Google Analytics 360 in providing actionable insights regarding your website’s performance and the usefulness of data warehouses like Snowflake and two methods on how to connect Google Analytics 360 to Snowflake. These data insights play a significant role in tracking your business’s success. Connecting Google Analytics 360 to cloud data warehouses as Snowflake enables you to use more advanced analytical tools and features.

However, as a Developer, extracting complex data from a diverse set of data sources like Databases, CRMs, Project management Tools, Streaming Services, and Marketing Platforms to your Database can seem to be quite challenging. If you are from non-technical background or are new in the game of data warehouse and analytics, Hevo can help!

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Hevo will automate your data transfer process, hence allowing you to focus on other aspects of your business like Analytics, Customer Management, etc. Hevo provides a wide range of sources – 150+ Data Sources (including 40+ Free Sources) – that connect with over 15+ Destinations. It will provide you with a seamless experience and make your work life much easier.

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