Nowadays, data has become one of the most priceless assets for any business model. Companies are using data in various aspects but as their business grows, the idea of storing all that data in a secure and centralized location becomes a huge question to them. This is where a Cloud-based Data Warehouse comes into the picture.

A Cloud-based Data Warehouse loads all your data into a centralized location gives you the privilege of on-demand computing, increased computing capacity, and seemingly limitless storage capacity. One of the leading Cloud-based Data Warehousing solutions is Snowflake, and if you’re looking for ways to load data from various sources to Snowflake, you’ve come to the right place. In this article, we’ll talk about GitHub Snowflake integration and its advantages.

Snowflake allows you to extract data from multiple locations, transform that data into a specific format and then store it into a centralized location. GitHub Snowflake Integration is one of the most popular integrations out in the market which developers majorly use to store their project data and use it comfortably as, when, and where required.

Now, let’s dive right into the article to learn about the ways to load data from GitHub to Snowflake.

Methods to Set Up GitHub Snowflake Integration

Method 1: Setting Up GitHub Snowflake Integration using Hevo

Hevo provides a hassle-free solution that helps you set up GitHub Snowflake Integration without any intervention in an effortless manner for free. 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. 

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Method 2: Setting Up Manual GitHub Snowflake Integration

This method entails manually setting up GitHub Snowflake Integration. The method is divided into 2 major parts. In the first part, you will have to manually export GitHub data in CSV format using custom scripts and then in the second part, you will have to import that data into your Snowflake Data Warehouse. This method demands technical proficiency and working experience in GitHub and Snowflake platforms.

Methods to Set Up GitHub Snowflake Integration

Since you already have a basic understanding of Github and Snowflake, let’s walk through the methods to set up GitHub Snowflake Integration. Also, read this article to find more information on Snowflake data streaming.

The first method uses Hevo, which is one of the best No-code Data Pipeline platforms, while the second method uses manual integration to set up GitHub Snowflake Integration.

Let’s walk through these methods one-by-one in detail.

Method 1: Setting Up GitHub Snowflake Integration using Hevo

Hevo Data, a No-code Data Pipeline, helps to Load Data from any data source such as Databases, SaaS applications, Cloud Storage, SDKs, and Streaming Services and simplifies the ETL process. It supports 150+ data sources, including GitHub, etc., for free and is a 3-step process by just selecting the data source, providing valid credentials, and choosing the destination. Hevo loads the data onto the desired Data Warehouse, enriches the data, and transforms it into an analysis-ready form without writing a single line of code.

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Here is a step by step guide to connect github to snowflake using Hevo. 

Step 1: Select the Source 

Github Snowflake Integration: Github as a Source

Hevo can connect to your GitHub account and transfer data to your Destination using Webhooks. Check out Hevo’s official documentation for more details. You can also learn more about how Webhooks work in GitHub here

Step 2: Select Snowflake as Destination

Here are the steps to setup Snowflake as the destination. 

  • Login and Configure your Snowflake Account. You will need to use our custom scripts, which you can find here
  • Obtain your Snowflake Account URL. 
  • Next, configure Snowflake as the destination.
Github Snowflake Integration: Snowflake as a Destination

For more information, check out the official documentations. 

Check out what the Analytics Engineer of Ebury, a Global FinTech company has to say about using Hevo for all their data integration needs:

With Hevo, our data is more reliable as it was compared to Fivetran at a way better Hevo Pricing. Hevo allows us to build complex pipelines with ease and after factoring in the excellent customer service and reverse ETL functionality, it is undoubtedly the best solution available in the market. 

– Juan Ramos, Analytics Engineer, Ebury
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Method 2: Setting Up Manual GitHub Snowflake Integration

Follow the steps below to set up GitHub Snowflake Integration manually:

Step 1: Export Files from GitHub in CSV Format

Follow the steps below to export the files from GitHub in CSV format:

  • Log in to your GitHub account and go to the project repository.
  • Go to the file you want to export. You can also view the content of the file within the GitHub User Interface (UI). Click on the file to view its content.
  • Now, right-click the “Raw” button. You will find this button at the top right corner of your screen.
  • Once done, click on “Save as”. Click on the location where you want to save this file after giving it a name of your choice.

Step 2: Import the Files into Snowflake Data Warehouse

Now, that you have exported all the files, it’s time to import these files into Snowflake Data Warehouse. Here, you will be using the PUT SQL command to load your CSV data file from your local system to Snowflake Internal Stage and then you will be using the COPY INTO SQL command to load the file from Snowflake Internal Stage to Snowflake Database Table.

Follow the steps below to import the files into Snowflake Data Warehouse and set up GitHub Snowflake Integration:

  • Upload the CSV file from the local system to Snowflake Internal Stage using the PUT SQL command. Use the following SQL query for the same.
    NOTE: By default, the PUT command compresses your file using GZIP.
PUT file:///apps/sparkbyexamples/emp.csv @%EMP;
  • Now, load the CSV file from Snowflake Internal Stage to Snowflake Table using the COPY INTO SQL command. For this step, first, you will have to create a Snowflake Table. Use the following SQL query to create a new Snowflake Table.
    NOTE: Change the column names as per your requirement.
CREATE TABLE EMP 
      (FNAME VARCHAR, LNAME VARCHAR,
       SALARY VARCHAR, DEPARTMENT varchar,
       GENDER varchar);
  • Now use the COPY INTO SQL command to load the file that you compressed in the last step into Snowflake Table that you created just now. Use the following for the same:
COPY INTO EMP from '@%EMP/emp.csv.gz';

That’s it. You have successfully set up manual GitHub Snowflake Integration.

Limitations of Setting Up Manual GitHub Snowflake Integration

Listed below are the limitations of manually setting up GitHub Snowflake Integration:

  • Setting up Manual GitHub Snowflake Integration requires technical expertise and experience in working with both GitHub and Snowflake. It would be very difficult for anyone with no or little technical experience to successfully integrate these 2 platforms.
  • As you will need to export and import data periodically, there is a high possibility of Data Redundancy.
  • Manual Integration is only effective when you have files in CSV format. If that is not the case, then it would be impossible to set up GitHub Snowflake Integration.

To avoid these limitations, you can set up GitHub Snowflake Integration using Hevo as it is a seamless and hassle-free integration method.

Advantages of Integrating GitHub Snowflake

Listed below are some of the major advantages of setting up GitHub Snowflake Integration:

  • GitHub Snowflake Integration allows you to store all the historical data in a centralized location. This makes it easier for you to fetch this information as and when required. Moreover, it also allows you to run this data through Business Intelligence tools and extract meaningful insights out of it.
  • As all your data will be stored in a centralized location, this will allow everyone in your team to use that data without even downloading it. The data could be huge and the elimination of the step where you had to download it for future use, makes it so much easier for you to use the data in your projects.

Conclusion

The article introduced you to GitHub Snowflake Integration and provided you with a comprehensive guide that you can use while setting up GitHub Snowflake Integration. The article included 2 different approaches to set up GitHub Snowflake Integration. The first method uses Hevo Data No-code Data Pipeline for automated integration while the second method is completely manual.

With the complexity involves in Manual Integration, businesses are leaning more towards Automated Integration. This is not only hassle-free but also easy to operate and does not require any technical proficiency. In such a case, Hevo Data is the right choice for you! It will help simplify the ETL Process process by setting up GitHub Snowflake Integration for free.

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Share your experience setting up GitHub Snowflake Integration in the comments section below!

Karan Singh Pokhariya
Former Research Analyst, Hevo Data

Karan has experience in driving strategic planning, and implementing data-driven initiatives. His experience spans strategic transition planning, data analysis for optimization, product development. His passion to data drives him write in-depth articles on data integration.

mm
Customer Experience Engineer, Hevo

Vinita, a Customer Experience Engineer, drives success through impactful training sessions and comprehensive documentation, enhancing team efficiency. With expertise in data pipelines and data warehousing, she excels in delivering top-notch customer support and multitasking efficiently.

No-code Data Pipeline for Snowflake