This spring, we introduced the 2023 edition of the Dataiku Frontrunner Awards, our annual competition that recognizes the achievements of data science practitioners across industries. With the submission deadline recently extended until August 1, it’s the perfect time to consider sharing your use case or success story with Dataiku. Continue reading to discover the benefits of participating and be inspired by recent entries to this year’s edition.
Benefits of Participating in the Dataiku Frontrunner 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 celebrate their success and share their achievements with the wider data science community.
There are several benefits associated with participating in the competition, including:
- 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 swap 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. However, this year we’re pleased to introduce “Community Choice,” a special distinction determined not by the panel but by peers from the Dataiku Community. All Dataiku Community members can give and receive votes, offering a unique opportunity to participate in the competition, even if they don’t plan to submit.
Be Inspired by Submissions for 2023
Submissions for this year’s edition of the awards are beginning to trickle in, showcasing the diverse ways in which individuals and organizations across industries are paving the way for Everyday AI. Discover a few early submissions below, and be inspired to enter your own use case or success story.
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.
To address these issues, precisely estimate the drill time of a well campaign, and maximize win rates of profitable bids, their team leveraged Dataiku to build NLP services, web applications, and ETL pipelines. Together, these provide SLB with a data-driven way to predict the time and risks associated with well construction when responding to a tender. The application is now part of standard operating procedures, with the approach used to assess over $10 billion worth of well construction tenders.
“Billion-dollar decisions are now data-driven while keeping our well engineering experts in control of the outcome,” explains Valerian Guillot, Data Science Technical Lead at SLB. “The web application also provides SLB engineers with tangible time efficiency gains. Manual efforts to analyze legacy data are now divided by 25. Whereas manually classifying a well previously took approximately eight hours, the same can now be achieved in 20 minutes.”
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, they 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.
“The Dataiku platform has allowed a small team to work efficiently and produce highly advanced results in a relatively short period of time,” explains the team. “The transparent, easily explainable workflow and results make it easier to get acceptance and understanding from both leaders and workers influenced by automation.”
Denarius Conseils & Gestion SA: Developing an End-to-end Platform to Scan Multiple Markets and Systematize the Investment Process
With an investment style involving highly active trading across multiple markets, a key challenge for portfolio managers at Denarius Conseils & Gestion SA was to simultaneously analyze all the markets they trade, detecting opportunities, patterns, and trends to generate investment ideas and define their macro view of the markets. Unfortunately, this was limited by manual analysis of each individual security and a lack of a centralized and collaborative environment for R&D.
Leveraging Dataiku, their team was able to develop a complex end-to-end platform, allowing for a fully automated trend-following strategy that can be integrated into portfolios, a rapid overview of market opportunities, and the possibility to spot trading signals in stocks and sectors that would typically not be considered a core area for investments.
“Dataiku has had a major impact on our ability to scan multiple markets and make our investment process more systematic,” says Alessandro Taglietti, Data Scientist and Portfolio Manager at Denarius Conseils & Gestion SA. “Every night, Dataiku analyzes more than 3,000 securities and markets for signals, patterns, and trends, producing a report for our traders indicating trends in key markets and highlighting securities that are attractive to trade.”