Enhancing Enterprise Data Engineering Workflows with AI-Powered Code Assistants: A Case Study on GitHub Copilot

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Niranjan Reddy Rachamala

Abstract

The case study explores setting up GitHub Copilot, an AI code suggestion tool, in companies that develop and test enterprise data systems to boost their work efficiency. Through the review of literature published until 2020, the study discovers that software developer’s face some issues, including repeating certain actions, inefficient projects and a lack of smart-thinking environments. The study shows that GitHub Copilot helps meet software development challenges by offering real-time, suitable code suggestions for each task in the Software Development Lifecycle (SDLC). The discussion demonstrates that using the tool can lead to more automated work, fewer errors and quicker tests. At the end of the study, there are suggestions for further research, involving evaluating outcomes, adjusting for each area and considering social aspects of using AI in businesses.

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References

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