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1
Intro
2
What do we see
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Who wants to analyze GitHub
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How GitHub events started
5
Google BigQuery
6
Comparing projects
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Looking for stars
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Looking at other projects
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Text analysis
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Country analysis
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New Zealand
12
Weather
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Code analysis
14
Stack Overflow
15
Go Query
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Static Code Analysis
17
Questions
18
Query Analysis
Description:
Explore the vast world of GitHub data through a comprehensive analysis of 750 billion events and 42 TB of code. Dive into insights on software development trends, open source community dynamics, and coding patterns over time. Learn how to leverage this rich dataset to guide project design decisions, request features based on data, and measure community health. Discover the most effective ways to phrase change requests and understand the impact of social media on project popularity. Investigate who starred your project and their other interests. Gain practical knowledge on running static code analysis at scale and settle the age-old debate of tabs vs. spaces. Presented by Felipe Hoffa, a Google Developer Advocate, this talk offers a deep dive into the world of big data analysis using Google Cloud Platform tools, demonstrating how to extract valuable insights from one of the largest datasets of collaborative software development.

What Can We Learn from 750 Billion GitHub Events and 42 TB of Code

Devoxx
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