Factored’s Datathon 2023

Factored’s Datathon 2023

Factored hosted its first virtual Datathon for all of Latin America.

What is a Datathon? It’s an event that brings together people to collaborate on a data-related challenge or problem. Essentially, participants work together to: 

  1. Extract, organize, catalog and clean data from multiple sources.
  2. Analyze and interpret data.
  3. Use this information to develop insights, solutions, and visualizations to drive and deliver impactful decisions.

In this post, we’ll share how the event was set up, the challenge participants worked on, the prize they were working for, and the feedback we received post-event.

Why Host a Datathon?

Datathons can create awareness and community between Data Analysts, Data Engineers, Machine Learning Engineers, and Software Engineers alike. It can also be a valuable forum in which hiring companies can identify talent, solve business problems, create awareness, and build community.

In order to attend, all participants must follow a Code of Conduct, which creates an environment free of harassment, discrimination, plagiarism or reusing of past work, and recording without consent.

How It Works

First, Factored created a challenge for participants. This was to create innovative data solutions (web apps, chatbots, dashboards, model interfaces, etc.) that empower businesses by generating insights from product reviews. Ideally, these data products would help solve a wide range of business problems, including—but not limited to—product optimization and marketing budget allocation, amongst others. 

Each team received a set of Amazon reviews from various products in different industries, and they represented a product company’s data team. They had to develop an end-to-end data product that was able to analyze all product reviews and generate actionable insights to inform stakeholders’ decisions.

The Incentive

Overall, 446 people registered for the event, making up 131 total teams, and participated for the chance to win three prizes: 

  • 1st place: US$5,000
  • 2nd place: US$2,500
  • 3rd place: US$1,500

In addition, they could win an opportunity to be interviewed by Factored.

Getting to Work

The Datathon event lasted 13 days, with one kick-off day and 12 coding days. Participants had a daily three hour window in which they were able to make submissions. All of the delivered products were top quality, meaning teams succeeded in developing usable solutions. Ultimately, each team delivered a presentation and a tool, all organized in a Github repository.

Coaching

Sharing knowledge is key to maintaining engagement and lowering the operational cost of mentoring. Setting up common spaces where participants can share their issues helps to create a knowledge repository where they can go back if they have issues.

We managed to coach the event with a total of 17 mentors who were Factored volunteers. This was achieved by setting slack channels up by topics. These channels were divided by sections where participants left their technical questions, including those related to data analytics, data engineering, and machine learning. Questions were answered by Factored mentors within 24 hours.

An event like this can be a great test environment to develop skills for the organizing team with low risk. In this case, setting up Data Streaming proved to be very valuable for the Factored Team.

Post-Event

After the event, we surveyed participants and the preliminary results showed the following: 

  • 3.92/5.00: Would recommend the event again
  • 3.95/5.00: Difficulty Level
  • 3.70/5.00: Support received
  • 2.80/5.00: Length of the event (Too short: 1, ideal: 3, Too long: 5)

Ultimately, we learned that over 50% of participants joined to learn and develop skills, and that more efforts can be made towards making it a more accessible event in the future (e.g. including aids for visually-and hearing-impaired people).

Does this sound like something you’d be interested in joining next year? Join the waitlist for our 2024 version by clicking the button below.

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