Scientific Data Analysis Pipelines and ReproducibilityPhoto by Campaign Creators on UnsplashWhat do pipelines do? Why do we need them?Pipelines are computational tools of convenience. Data analysis usually requires data acquisition, quality check, clean up, exploratory analysis and hypothesis driven analysis. Pipelines can automate these steps. They process raw data to a suitable format and analyze it with statistical tools or machine learning models
