Tom Brown (41xRT) - Helping Nonprofits Leverage Insights From Their Data

tgb417 Dataiku DSS Core Designer, Dataiku DSS & SQL, Dataiku DSS ML Practitioner, Dataiku DSS Core Concepts, Neuron 2020, Neuron, Registered, Dataiku Frontrunner Awards 2021 Finalist, Neuron 2021, Neuron 2022, Frontrunner 2022 Finalist, Frontrunner 2022 Winner, Dataiku Frontrunner Awards 2021 Participant, Frontrunner 2022 Participant, Neuron 2023 Posts: 1,595 Neuron

Tom Brown

Non Profit Data Science & Analytics Advocate

United States


41xRT is “Where Arts and Technology Meet”. This is a name that I use while working with Cultural Non-Profit Organizations either with data technology, group facilitation or his own computational art work. In this context, I typically work on opportunities to allow data from patrons to speak more clearly to organizations helping them take smarter actions. Almost all of the work that I have done with organizations is on a pro bono basis helping the organizations build new data oriented capabilities.

Awards Categories:

  • Organizational Transformation
  • Data Science for Good
  • AI Democratization & Inclusivity
  • Alan Tuning


As a personal passion, and professional mission, I am helping non-profit organizations around the world better understand their stakeholders through data and take actions based on these insights. Two challenges commonly arising when it comes to data science in the non-profits sector, particularly when trying to move beyond basic monitoring and evaluation toward the use of predictive models to drive more productive action:

1. Lack of proper infrastructure for data management & analysis

As a striking example, when I started contributing to data analysis for a community college a few years ago, the collection pipeline was... making tick marks on a sheet of paper and having a work study student convert those tick marks to a spreadsheet! This was then used to produce end-of-year summary reporting.

That is at the extreme end, to be sure, but many grassroots organizations rely on Excel spreadsheets. Even the largest cultural non-profit organizations don’t typically have data science tools to support the building of data pipelines and predictive modeling.

2. Vision and skills challenge for data science & AI

The second challenge reflects a deeper issue of stakeholders’ awareness and ability to understand what data science is, what value it can bring, and what is possible through model operationalization to drive optimal action. In an already-tense market, it is difficult for nonprofits to hire for specialty data skills, especially as they have historically placed a priority on hiring more for “people skills”, including word literacy, fundraising, and passion for mission, than to build models that drive optimal performance.


Hence my work revolves around pro bono consulting to build awareness and capabilities around how nonprofits think about data, data pipelines, and predictive analytics for their organizations - and Dataiku as a company, community, and tool has in so many ways helped move these endeavors forward.

1. Cleaning data for visualization at a Community college

I started using the free version of Dataiku back in early 2017 (version 3) for a project with a Community College. This project enabled me to develop my own awareness of data science and tools that were accessible to non-programers. During this project, I used the visual recipes to turn messy data into clean data for visualization.

The first major project helped the library to understand seasonal student flow at the reference desk. This understanding allowed staff to improve staffing levels at needed times to improve the student experience.

2. Predicting attendance at a children science museum

Then, I brought Dataiku to Liberty Science Center, where I was spearheading Digital Projects & Analytics, and they benefited from the donated license as part of the Ikigai program. Our initial objective was to forecast future year attendance. Thanks to Dataiku resources and the versatility of the platform, we grew our data science skills to create features and develop a model that confirmed some staff hunches: at a children's science museum, attendance is strongly correlated with weather! Through simulating future years based on 20 years of past weather data, we found upper and lower bounds on attendance to inform the annual budgeting process.

Our next project, which started just before COVID-19 hit, was to use the pipeline features to manage customer records in the fundraising and ticketing CRM system.

3. Equipping nonprofits with data science they can use

Subsequently, I helped various non-profit organizations design and implement data science projects using Dataiku, which provides an interface to operationalize and leverage part of the work for other data initiatives. From cleaning data to re-import into the CRM system of Synchronicity for a women-run theater in Georgia, to audience segmentation and retention projects for the Cascade Bicycle Club, and membership churn modeling for a children's museum in Minnesota.

4. Building communities to share data science knowledge & learnings

To expand my own knowledge throughout these endeavors, I sought to exchange with peers in the industry. That involves hosting events for the Dataiku New York User Groups, helping users solve their issues on the Dataiku Community as a Dataiku Neuron, facilitating an ‘analytic Coffee’ group, as well as an study group among cultural non-profit administrators. Each of these activities helps to build awareness and capabilities for myself and emerging nonprofit leaders that now better understand the value of data science to facilitate smarter action.


Data science is still at the infancy stage for most non-profit organizations. With Dataiku and a growing expertise to develop projects, enable team members, and communicate value to stakeholders, I was able to:

1. Deliver projects into organizations which wouldn’t have tackled them by themselves

All projects listed above resulted from challenges known by nonprofits, but they did not have the awareness, the technology, nor the skills to solve. Having a single platform to build and operationalize projects enabled us to build solutions which wouldn’t be possible with the previously manual spreadsheet work.

2. Convert data into practical insights for the organizations

Dataiku’s visualization features proved invaluable to communicate insights from data analysis to the broader organizations. This was key to show the value of data science initiatives, and enable further investment from staff in time and resources.

3. Build repositories of data science projects to leverage for future endeavors

With the visual interface, workflows become understandable - even for non-data literate team members. This enables everyone to build upon existing work from more technical people, and leverage parts of it to conduct their own projects.

4. Onboard, enable, and upskills staff members and volunteers to leverage more insights from their data

Thanks to the user-friendly interface, online resources, and programs such as Ikigai which provided a full-featured license and training, I was not only able to bring data science into all these organizations - but more importantly provide a pathway for them to build their own vision of what data science can bring to them.

Users are quickly able to learn new data skills, and some have started to produce their own insights and build more advanced projects to grow their organizations. Although we’re living in a world of data science, most non-profit organizations still have a long way to go to embed the value of data science into their organizations and reap the benefits of smarter stakeholder interactions.

With Dataiku, I have been planting the seeds of data democratization, enabling more stakeholders to leverage it and enable organizational change to fulfill their mission and change the world for the betterment of all.

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