Google Drive to Snowflake: 2 Easy Ways

• September 19th, 2022

Google Drive to Snowflake - Featured Image

As a data engineer, you hold all the cards to make data easily and timely accessible to your business teams. Your marketing, sales, & finance teams just requested a Google Drive to Snowflake connection on priority to quickly replicate their spreadsheets data. We know you don’t wanna keep your data scientists and business analysts waiting to get critical business insights.

As the most direct approach, you can go straight to downloading data from Google Drive and uploading it to Snowflake if this is a one-time thing. Or, hunt for a no-code Tool that fully automates & manages data integration for you while you focus on your core objectives.

Well, look no further. With this article, get a step-by-step guide to connect Google Drive to Snowflake effectively and quickly deliver data to your marketing team.

Table of Contents

How to connect Google Drive to Snowflake?

Exporting & Importing spreadsheets as CSV Files

To replicate data from Google Drive to Snowflake, you can follow the steps given below:

  • Step 1: Data can be present in Google Drive as spreadsheets in the form of Google Sheets, Excel & CSV files. Select the required files and download your data in CSV format to your local system. You can first convert your responses as a Google Sheet for Google Forms and follow the same procedure. 
  • Step 2: Log in to your Snowflake Account and select the database where you want to upload the files. Use the Create or Replace FILE FORMAT command to create a named file format for CSV. 
use database test_db;
create or replace file format new_csv_format
  type = csv
  field_delimiter = ','
  skip_header = 1
  null_if = ('NULL', 'null')
  empty_field_as_null = true
  compression = gzip;
  • Step 3: Assuming no destination table exists, use the create or replace table command to create the new table.
CREATE OR REPLACE TABLE test_students (
student_ID number,
First_Name varchar(25),
Last_Name varchar(25),
Admission_Date DATE
);
  • Step 4: Now, load the CSV file into the staging area of Snowflake using the PUT command.
put file://D:\test_stud.csv @test_db.PUBLIC.%test_students;
  • Step 5: Load the data into your target table using the COPY INTO command.  
copy into test_students
from @%test_students
file_format = (format_name = 'new_csv_format' , error_on_column_count_mismatch=false)
pattern = '.*test_stud.csv.gz'
on_error = 'skip_file';

This 5 step hands-on approach is a great way to effectively replicate data from Google Drive to Snowflake using CSV files and SQL Queries. It is optimal for the following scenarios:

  • One-Time Data Replication: When your business teams need this Google Drive data only quarterly, yearly, or just this one time, then the manual effort & time is justified.
  • No Data Transformation Required: This approach has limited options in terms of data transformation. Hence, it is ideal if the data in your spreadsheets is clean, standardized, and present in an analysis-ready form.
  • Less Number of Files: Downloading & writing SQL queries to upload several CSV files is a time-intensive job. It can be especially tedious if you need to generate a 360 view of the business and merge spreadsheets containing data from multiple departments across the firm.   

Though, if you want to leverage the power of complete data from multiple sources apart from Google Drive, manually downloading & transforming the files doesn’t make sense. You would need to develop custom connectors and manage the data pipeline always to ensure a no data loss transfer. It also includes you continuously monitoring for any updates on the connector and being on-call to fix pipeline issues anytime. With most of the raw data being unclean and in multiple formats, setting up transformations for all these sources is another challenge. 

A great alternative is to try out a No-code tool that completely automates the Google Drive to Snowflake ETL/ELT process and manages it for you. 

Automate the Data Replication process using a No-Code Tool

Using manual scripts and custom code to replicate data from Google Drive to Snowflake is cumbersome. Frequent breakages, pipeline errors, and lack of data flow monitoring make scaling such a system a nightmare.

An automated tool is an efficient and economical choice that takes away months of manual work. It has the following benefits:

  • Allows you to focus on core engineering objectives while your business teams can jump on to reporting without any delays or data dependency on you.
  • Your marketers can effortlessly enrich, filter, aggregate, and segment raw Google Drive data with just a few clicks.
  • The beginner-friendly UI saves the engineering teams’ bandwidth from tedious data preparation tasks.
  • Without technical knowledge, your analysts can seamlessly standardize timezones, convert currencies, or simply aggregate campaign data for faster analysis. 

For instance, here’s how Hevo, a cloud-based ETL tool, makes Google Drive to Snowflake data replication ridiculously easy:

  • Step 1: To replicate data from Google Drive to Snowflake, you can first configure Google Drive as a source by connecting to your Google account.
Google Drive to Snowflake - Sign in using Google Account
Image Source
  • Step 2: Now, provide a unique name for your pipeline and select the folders/files you want to replicate. 
Google Drive to Snowflake - Select Folders
Image Source
  • Step 3: To complete the process of replicating data from Google Drive to Snowflake, you can start by providing your Snowflake credentials. 
Google Drive to Snowflake - Add snowflake credentials
Image Source

In a matter of minutes, you can complete this No-Code & automated approach of connecting Google Drive to Snowflake using Hevo and start analyzing your data.

Hevo offers 150+ plug-and-play connectors(Including 40+ free sources like Google Drive). It efficiently replicates your data from Google Drive to Snowflake, databases, data warehouses, or a destination of your choice in a completely hassle-free & automated manner. Hevo’s fault-tolerant architecture ensures that the data is handled securely and consistently with zero data loss. It also enriches the data and transforms it into an analysis-ready form without having to write a single line of code.

Hevo’s reliable data pipeline platform enables you to set up zero-code and zero-maintenance data pipelines that just work. By employing Hevo to simplify your data integration needs, you get to leverage its salient features:

  • Managed Data Warehouse: With Google Drive as your source, Hevo provides you with a fully managed BigQuery data warehouse as a possible Destination.
  • Reliability at Scale: With Hevo, you get a world-class fault-tolerant architecture that scales with zero data loss and low latency. 
  • Monitoring and Observability: Monitor pipeline health with intuitive dashboards that reveal every stat of pipeline and data flow. Bring real-time visibility into your ELT with Alerts and Activity Logs. 
  • Stay in Total Control: When automation isn’t enough, Hevo offers flexibility – data ingestion modes, ingestion, and load frequency, JSON parsing, destination workbench, custom schema management, and much more – for you to have total control.    
  • Auto-Schema Management: Correcting improper schema after the data is loaded into your warehouse is challenging. Hevo automatically maps the source schema with the destination warehouse so that you don’t face the pain of schema errors.
  • 24×7 Customer Support: With Hevo, you get more than just a platform, you get a partner for your pipelines. Discover peace with round-the-clock “Live Chat” within the platform. What’s more, you get 24×7 support even during the 14-day full-feature free trial.
  • Transparent Pricing: Say goodbye to complex and hidden pricing models. Hevo’s Transparent Pricing brings complete visibility to your ELT spend. Choose a plan based on your business needs. Stay in control with spend alerts and configurable credit limits for unforeseen spikes in the data flow. 
GET STARTED WITH HEVO FOR FREE

What can you achieve by migrating your data from Google Drive to Snowflake?

Here’s a little something for the data analyst on your team. We’ve mentioned a few core insights you could get by replicating data from Google Drive to Snowflake, does your use case make the list?

  • Know your customer: Get a unified view of your customer journey by combing data from all your channels and user touchpoints. Easily visualize each stage of your sales funnel and quickly derive actionable insights.   
  • Supercharge your conversion rates: Leverage analysis-ready impressions, website visits, & clicks data from multiple sources in a single place. Understand what content works best for you and double down on it to increase conversions.
  • Boost Marketing ROI: With detailed campaign reports at your grasp in near-real time, reallocate your budget to the most effective Ad strategy.  

Summing It All Together

Exporting and importing CSV files is the right path for you when your marketing & sales teams need data from Google drive once in a while. However, a custom ETL solution becomes necessary for real-time data demands such as monitoring campaign performance or viewing the recent user interaction with your product or marketing channel. You can free your engineering bandwidth from these repetitive & resource-intensive tasks by selecting Hevo’s 150+ plug-and-play integrations.

Visit our Website to Explore Hevo

Saving countless hours of manual data cleaning & standardizing, Hevo’s pre-load data transformations get it done in minutes via a simple drag n drop interface or your custom python scripts. No need to go to your data warehouse for post-load transformations. You can simply run complex SQL transformations from the comfort of Hevo’s interface and get your data in the final analysis-ready form. 

Want to take Hevo for a ride? Sign Up for a 14-day free trial and simplify your data integration process. Check out the pricing details to understand which plan fulfills all your business needs.

Share your experience of connecting Google Drive to Snowflake! Let us know in the comments section below!

No-code Data Pipeline for Snowflake