Leaders and Top Use Cases in AI: 2021

Use Cases & Projects, Dataiku Product Lisa Bardet

We launched the Dataiku Frontrunner Awards to celebrate the data science and AI builders who are doing the nitty gritty work to drive the field forward, day in and day out. 

This first edition gathered an outstanding number of detailed use cases from data practitioners and leaders around the world —  45 to be exact. The stories come from organizations of all industries and sizes who are pioneering collective success in data science and AI. 

This impressed the Dataiku executives and industry experts who gathered as a jury to review and rate each submission. They recognized 9 winners and 16 finalists who are paving the way in their industry, from transforming legacy banking systems to building Responsible AI tools to democratizing customer insights. Read on to learn from their achievements!

award winners

Organizational Transformation Award

Standard Chartered Bank (Craig Turrell, Head of Digital Centre of Excellence P2P)

Craig’s team is replacing spreadsheet-based processes with governed self-service analytics to build intelligent data operations for financial planning and performance management. On average, two people armed with the Digital MI team's applications in Dataiku are now doing the work of about 70 people limited to spreadsheets turning data insights into a commodity for thousands of stakeholders across the leading international banking group.


AI Democratization Award

SLB (Valerian Guillot, Nerve Center Data Science Architect)

As a major actor of the global energy industry, SLB is paving the way in democratizing AI within the organization. They’re leveraging Dataiku to enable all people, regardless of their profile, to gain insights from their data thanks to a successful mix of data access helpers, a variety of custom training, and community-based technical support.

activity of users per job code


Data Science for Good Award

Atlantic Plant Maintenance (Aaron Crouch, Data Analytics Manager)

The data team at Atlantic Plant Maintenance faces a titanic challenge, as the repair and maintenance of power plant equipment represents a very difficult and dangerous job for union workers. They sought to use the data at their disposal to bring workers home safe through defect detection flagging problem jobs and trying to prevent an incident before it happens. In three years, they were able to decrease the proportion of safety or quality defects from 26% to less than 11%, increasing the safety of workers who might otherwise have been hurt. 


Responsible AI Award

Unilever (Linda Hoeberigs, Head of Data Science and AI, PDC Lab & Ash Tapia, Data Partnerships & Tools Stack Manager)

Keeping a pulse on customer insights is key for Unilever to stay on top of the latest industry trends — but how can we ensure that those are free of any unintended bias? The central data team designed a responsible, self-service tool for Natural Language Processing (NLP), which was recognized by an external AI auditing firm as not only responsible in its development, but also in the way it is used by analysts worldwide. 


Value at Scale Award

NXP Semiconductors (Adnan Chowdhury, Manufacturing Quality Engineer)

In semiconductor manufacturing, a critical quality is the ability to detect and resolve manufacturing issues as quickly as possible. Adnan and his team have implemented a pioneering method and machine learning model to reduce the detection time-to-detect with real-time automated process control, leading to savings in the million dollars based on material and engineering costs.


Value at Scale Award

Royal Bank of Canada (Masood Ali, Senior Director, Data Strategy & Governance)

With 400 internal entities, compiling the annual audit plan used to be a resource-intensive manual process spanning several months. Meet RaptOR, a tool built by the RBC team for dynamic audit planning through machine learning-based risk assessment, which enables an automated, data-driven risk assessment process. This triggered operational efficiencies for the entire Internal Audit department, as well as quicker adjustments to the audit plan to respond to changes in the risk environment. 


Excellence in Teaching Award

HES-SO (Cédric Gaspoz & Dominique Genoud, Professors)

Professors Cédric Gaspoz and Dominique Genoud are teaching the next generation of Chief Data Officers not only about analyzing data, as in traditional business intelligence courses, but also on becoming information producers. In one year, 109 users in 39 groups have created 646 projects in Dataiku via remote collaboration — which enabled them to manage the end-to-end workflow, upskill in desired languages and technologies, and productionalize models as they would do in the business. 


Excellence in Research Award

Researcher Frank Romo and Professor Harley Etienne (University of Michigan) 

As part of their research, Frank Romo and Harley Etienne took on the gigantic challenge of mapping police fatal encounters in the United States between the years 2015 and 2020, which involved cleaning, mapping, and analyzing thousands of records to build a comprehensive dataset, as well as perform spatial analysis, regressions, and static tests, to better understand their spatial distribution and inform future policy discussions.

race and policing in America


Alan Tuning Award

Malakoff Humanis (Nikola Lackovic, Data Scientist)

The data team at Malakoff Humanis, one of France's leading social protection groups, is leveraging AI to democratize insights from customer feedback. Their pioneering solution integrates speech recognition, NLP, automation features, and visualizations, as well as a new retro-feedback loop to further improve accuracy.  Not only does this equip more people with fresh customer insights, but it also leads to tremendous cost savings and an improved customer experience. 


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