Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY

InnerSource for reproducible and extensible business analysis

Emily Riederer (Capital One)
3:30pm–4:10pm Thursday, 09/13/2018
Data-driven business management, Strata Business Summit
Location: 1A 08 Level: Non-technical
Secondary topics:  Financial Services

Who is this presentation for?

  • Data scientists, data analysts, and business analysts

What you'll learn

  • Understand why designing empathetic analytical tools and fostering a vibrant InnerSource community are keys to developing reproducible and extensible business analysis


Data science and research communities are constantly evolving to incorporate new methodologies and tools to promote open, reproducible outputs. However, while business analysis has rapidly grown more data driven, the analyst community is slow to adapt to emerging best practices of reproducible and extensible workflows.

Emily Riederer maps common pain points in business analysis to established solutions from software engineering, data science, and the open science movement. Using a case study from Capital One, Emily discusses how designing empathetic, empowering, and engaging analytical tools is the key to igniting this organizational change and cultivating a sustainable InnerSource ecosystem.

Emily shares her experience building an opinionated R package to encapsulate common business analysis processes and encourage reproducible and extensible work. This required careful curation of tools, dependencies, and trade-offs to optimize over simplicity, efficiency, and transparency. Ultimately, it led to highly empathetic, user-driven design of intuitive, user-friendly workflows and a constantly evolving tool suite created entirely by business analysts.

Telling the parallel stories of package development and associate development, Emily outlines both design principles and key considerations for enterprise R packages and details best practices and lessons learned using the package to drive organizational change. You’ll also learn how Capital One demonstrated the value of this initiative to nontechnical stakeholders, upskilled associates with no coding background, and ultimately built an internal community of users and developers for a constantly growing suite of inner-sourced tools.

Photo of Emily Riederer

Emily Riederer

Capital One

Emily Riederer is an Analytics Manager at Capital One where she focuses on building opinionated data products to promote scalable and reproducible business analysis. At Capital One, she has worked across acquisitions and CRM credit strategy and led consulting initiatives for retail partners.

Outside of work, Emily is an active member of the #rstats community. Most recently, she has reviewed packages for rOpenSci and helped to co-organizer the first Chicago R unconference and the inaugural satRday Chicago conference.

Previously, Emily earned degrees Mathematics and Statistics / OR at the University of North Carolina at Chapel Hill. During her studies, she focused on healthcare analytics as a research assistant in emergency department discrete event simulation and a student consultant for a large managed healthcare provider.