Are you finding it difficult to connect GitHub to Tableau? Do you feel exhausted after writing endless lines of code & still not succeeding?
Don’t worry, we’ve got you covered!
This article will answer all your queries. Follow our easy step-by-step guide to help you master the skill of efficiently connecting GitHub to Tableau and performing insightful analysis.
Table of Contents
Hevo Data, a No-Code Data Pipeline, helps to transfer data from GitHub (Free Data Source) and 100+ sources to your desired data warehouse for free and visualize it in Tableau. 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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It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination. It allows you to focus on key business needs and perform insightful analysis using BI tools such as Tableau and many more.
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- Completely Managed Platform: Hevo is fully managed. You need not invest time and effort to maintain or monitor the infrastructure involved in executing codes.
- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
- Data Transformation: It provides a simple interface to perfect, modify, and enrich the data you want to export.
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Working knowledge of Tableau.
- Tableau installed at the host workstation.
- A GitHub repository.
- A GitHub account.
Connecting GitHub to Tableau
The purpose of connecting any application with Tableau is to visualize the data for analysis. Tableau requires data to be in an analysis-ready format. The best way is to create a database or use an existing data warehouse, upload data to it, & then connect it with Tableau for data analysis.
Tableau provides good flexibility and easily connects with a large variety of data warehouses. Its feature of locally caching data to process the queries faster makes the process of handling slow databases a lot easier.
There are many data warehouses such as Google BigQuery, PostgreSQL, Amazon Redshift, etc. with which GitHub can connect in just a few steps. All data warehouses have their set of procedures to set up a successful connection.
You can connect GitHub to Tableau using the following steps:
Step 1: Extracting Data From Github Using Rest API
GitHub has a REST API that can be used to retrieve information about projects, repositories, pull requests, and just about every other kind of data that it stores. For example, to get information about an issue, you would make the call as follows:
Once you have issued the call, you would get an output as follows:
"title": "Found a bug",
"body": "I'm having an issue.",
This is how you can extract data from GitHub using its REST API.
Step 2: Loading Github Data Into a Data Warehouse or Database
Once you have extracted data from GitHub, you need to select the desired destination to load this data and then connect it with Tableau to perform data analysis. Every database or data warehouse has its own set of steps that need to be carried out to connect successfully with Tableau.
If you’ve selected Google BigQuery as your destination, data can be loaded using the bq-command. This command also ensures that the schema & type information is correct. You can read more about loading data using this command and its limitations from the official documentation for Google BigQuery.
Similarly, PostgreSQL offers various methods to upload data depending upon the quantity of data. Insert & copy commands are used to load data in PostgreSQL. The insert command is useful for loading data in smaller chunks whereas, for bulk uploads, the copy command is the better choice. For further information on loading data into PostgreSQL, you can check the official documentation of PostgreSQL.
There are many data-warehouses such as Snowflake, Amazon Redshift, etc. that you choose as your desired destination and load your GitHub data to connect with Tableau.
This is how you can load data from GitHub to your desired data warehouse or database.
Step 3: Connecting a Database/Data Warehouse to Tableau
Launch Tableau on your workstation and select more from the connect column on the left. This will open a new window, from where you can select your desired data warehouse or database.
You can even choose the ODBC option if you want to connect using the ODBC connector of a particular database or data warehouse.
To connect with Tableau, you need to provide the credentials for your desired database or data warehouse such as your username, password, server, port number, etc. to successfully connect and load data into Tableau.
For example, if you select Amazon Redshift as your data warehouse, you will see the following connection dialog box on your screen once you’ve selected it.
This is how you can connect GitHub to Tableau by first loading your Github data into a desired database or data warehouse and then connecting it with Tableau.
This article teaches you how to transfer data from GitHub to Tableau. It also provides in-depth knowledge about the concepts behind every step to help you understand and implement them efficiently. Using APIs and executing ETL jobs can be challenging, especially for a beginner & this is where Hevo saves the day.
Hevo Data, a No-Code Data Pipeline, helps you transfer data from GitHub (Free Data Source) to a destination of your choice in a fully-automated and secure manner without having to write the code repeatedly for free. Hevo with its strong integration with 100+ sources & BI tools, allows you to not only export & load data but also transform & enrich your data & make it analysis-ready in a jiffy.
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Tell us about your experience connecting GitHub to Tableau! Share your thoughts with us in the comments section below.