Thinking about entering the 2023 edition of the Dataiku Frontrunner Awards, but uncertain about meeting the July 1st deadline? We’re pleased to announce that you have an extra month to participate, with submissions officially open from now until August 1st. It’s the perfect time to start putting together your own use case or success story to share with your peers and celebrate your achievements!
Continue reading to learn more about the benefits of participating, and be inspired by recent submissions to this year’s edition from your fellow Dataiku Community members.
Benefits of Participating in the Awards
Several winners and finalists from the 2022 edition of the competition being recognized onstage at Everyday AI Paris
Each year, Dataiku users of all types — including customers, partners, nonprofits, academics, and individual users — can take advantage of the unique opportunity that the Dataiku Frontrunner Awards presents to share their work with the wider data science community.
While there are many benefits that come with participating, some of the key ones include:
Gaining recognition as a thought leader: Communications and speaking opportunities enable winners and finalists to gain visibility in the industry, while all participants can gain exposure across Dataiku’s networks.
Celebrating individual and team success: Participants can inspire others by sharing their achievements and the value they’ve generated through their work with Dataiku, either individually or collectively.
Enhancing employer branding: By showcasing their innovation within the data science community, organizations can entice the best and brightest minds to join them and contribute to their success.
Winning special prizes and swag: Winners are offered a unique trophy and special Dataiku swag to thank them for their contributions to knowledge sharing.
Like in previous editions, winners and finalists will be determined by a panel of judges composed of Dataiku executives and independent industry experts. That said, we’d like to remind you that we recently introduced “Community Choice,” a special distinction determined not by the panel but by your peers. With all Dataiku Community members able to give and receive votes, it offers a unique opportunity to participate in the competition, even if you don’t plan to submit (though we’d highly encourage you to do so!).
Be Inspired by Recent Submissions
If you feel stuck when faced with the submission form, you don’t need to go any farther than recent entries to be inspired. Explore some of the recent submissions below, and don’t forget to give them a like or “kudos” to support them for Community Choice!
SLB - Sizing Billion USD Well Construction Tenders Using Web Application and Machine Learning Models
SLB offers integrated well construction services to operators, and one of the main services offered consists of the delivery of lump sum turnkey wells to customers at a fixed cost. The sizing of these opportunities ranges from millions to billions of dollars USD and are typically granted following a tendering process. It’s necessary they correctly size the response to the bid to ensure the project is profitable while providing competitive prices.
To do this, they must predict the time it will take to deliver the wells, understand the risks, and determine the cost of a well. However, this requires analysis of historical data, and the data is often stored in unstructured reports, while the turnaround time to respond to a tender is extremely short.
Frende Forsikring - Combing AI and Robotic Processes to Automate Claims Reporting
To make claims reporting as simple as possible for their customers, Norwegian insurance company Frende Forsikring used one common email address for reporting claims, despite having four different claim units. This required emails to be manually read, interpreted, and forwarded to the correct claim unit — a time-consuming, tedious process.
Recognizing it as the perfect case for automation, members from their AI/ML and Robotic Process Automation teams collaborated to develop a solution. After training a BERT model on around 10,000 emails to predict the correct unit for incoming emails, Anders Dræge (@Anders) and his team uploaded the trained model and tokenizer into Dataiku. The end result was a scalable, highly automated process that saves dozens of work hours each month and provides an improved customer experience.
ICAN Consultancy - Developing an ML Classifier Feature to Measure the Trust Score of Cryptocurrency Wallets
In the cryptocurrency industry, there a number of fraudulent activities occurring, with the identityless and immutable nature of blockchain making it very difficult to stop these things from occurring. What’s more, while there are good players in the ecosystem creating new products and services, there is less of a focus on the safety and security of using cryptocurrency wallets. This affects the attractiveness of the cryptocurrency and makes it almost impossible to generate high B2B revenue.
By leveraging Dataiku to add an ML classifier feature, Can Huzmeli (@can), Director of ICAN Consultancy, developed a trust score for an Ethereum wallet ID that measures the trustworthiness of a particular account. This helps cryptocurrency users to check the receiver party for their trust score before approving any payment, and stops illicit addresses from getting fraudulent payments from honest users. Over 100 users have received a trust score for their wallet within 90 days of the launch, with the service currently available free of charge.
Enter Your Submission to the 2023 Dataiku Frontrunner Awards
Explore recent submissions to the 2023 edition of the Dataiku Frontrunner Awards, or submit your own use case or success story with Dataiku before the August 1st deadline.