Objective: To perform a structured time-series analysis with causal inference to determine if the training provided to a software engineering team was the cause for a decrease in bugs reported.
Scenario: A streaming service, WebFlix, delivers its content through several channels: iOS app, Android app, Roku app, Fire TV app and web browsers. Each channel is managed by a different software engineering team. The engineering teams track the number of bugs reported each week and monitors patterns. Management of the Web team identified a worrying upwards trend in the number of bugs reported and provided training to the team in May 2020 to address the problem.
Tools Used: Python, Pandas, Matplotlib, Seaborn, Causal Impact
Skills Demonstrated: Exploratory Data Analysis, Bayesian Structural Time Series, Causal Inference, Data Visualization
Data Source: The CSV file contains weekly reporting of the number of bugs reported for each software engineering team in 2020. The data is synthetic and created for the purpose of this notebook.