Many case studies demonstrate the benefits of organizations developing internal R packages. But how do you move your organization from individual internal packages to a coherent internal ecosystem?
This talk will examine how internal R packages can drive the most value for their organization when they embrace an organization’s context, as opposed to open source packages which thrive with increasing abstraction.
We will first define an ontology of internal tools that perform different jobs-to-be-done, from an IT guy who heroically resolves proxy issues to a tech lead who democratizes tribal team knowledge.
Next, we will explore design principles and practices for internal packages and consider how these deviate from open-source standards due to organizations’ unique opportunities and constraints. Specifically, we will see how every aspect of a package's design -- from technical nuances like API design and error handling to big picture issues like documentation and testing -- can be used to encode context and make our packages more like valued and empowered teammates.
Participants should leave the discussion with a new framework for considering the design of internal R packages and a set of practical, easy to implement initial suggestions.
Emily Riederer is a Senior Analytics Manager at Capital One where she leads a team to develop and sustain data products (including data marts, analytical tools, and dashboards) for business analysts and executives. She is particularly passionate about bringing open source tools and culture to industry and empowering communities of practice within organizations.