Connect GitLab to Looker Studio
Confused on how to automate dashboard and Looker model deployment? Use Windsor to integrate Looker Studio and GitLab to gain access to automation of Models along with dashboards.
Why do I need GitLab and Looker Studio integration?
Integrating GitLab and Looker Studio can be beneficial for various reasons. As it allows enterprises to enable version control for their data modelling. Teams can collaborate using Gitlab’s collaboration feature such as code reviews, merge requests, and more. Most importantly, developers, stakeholders, and analysts gain access to live up-to-date looker data ensuring everyone is on the same page thus improving efficiency in the enterprise.
Version Control Feature
By integrating GitLab and Looker Studio, enterprises can make use of GitLab’s powerful version control system to manage its Looker Studio data as well. This can allow them to monitor the changes made, reverting to previous versions, and collaborating efficiently.
Collaboration and Development
GitLab’s collaboration capabilities such as merge request, code reviews, issue tracking can also be used on models and dashboards from Looker Studio. Each team member can access, ask for changes, and review other works while discussing on GitLab. This can prove to provide a very clear and transparent structure to the development project.
Automation
GitLab’s Continuous Integration/Continuous Development (CI/CD) can be used to automate the deployment of models and dashboards in the Looker Studio. This can help enterprises push for better efficiency in work as it streamlines the development process and also reduces manual error thus improving accuracy and consistency.
Compliance and Audit
By integrating the two platforms we can use GitLab’s version control feature to maintain a record of all the changes made to models and dashboards. This can be crucial for compliance and internal audits during development.
Efficient Workflow
Another important feature of integrating GitLab and Power BI is their capability to handle data in large quantities allowing the business to grow. Power BI allows for adaptability in its reports and visuals as expansion occurs while GitLab handles heavy data at the time of expansion. This gives the management flexibility as they plan to expand their business.
By integrating GitLab and Looker Studio, enterprises can simplify their workflow by centralizing development, version control, and deployment of models and dashboards. This can ultimately lead to better efficiency in the workplace and a better collaboration among teams.
Prerequisites
To set up the connector, the user should have:
- GitLab account (Visit our privacy policy and terms of use)
- Google account for Looker Studio integration.
How to connect GitLab to Looker Studio
1. Register
Register or login if you already have an account.
2. Select your source
You need to select GitLab as a Data Source and Grant Access to Windsor.ai.
3. Select the fields on the right.
Select the fields on the right to later use in your data source.
4. Select Destination
Go to “Select Destination” and Choose Looker Studio.
5. Sync and authorize data
Select “connect” and authorize access to your data source.
FAQs
What is GitLab?
GitLab is a centralized DevOps platform which combines Git repository management with a wide array of tools used for software development and collaboration. It works as a centralized space thus allowing team members to collaborate and work on projects efficiently. GtiLab’s main feature is its Git repository hosting that allows version control along with codebase collaboration. Taking everything into consideration, GitLab is a unified platform for teams to collaborate, develop, manage, and deploy software projects.
What is Looker Studio?
Looker Studio (formerly known as Google Data Studio) is an online data analytics tools that converts data into visually appealing reports. It possesses a number of features which allows its users to create analytical reports which can be easy-to-understand and allow the management to make data-driven decisions. It enables users to import data from multiple sources and export data in the form of interactive and visually appealing reports.
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