NEW YORK - April 9, 2019 - Dataiku, one of the world’s leading Enterprise AI and machine learning platforms, today announced its collaboration with GE Aviation through a joint white paper detailing the evolution of GE Aviation’s Enterprise AI journey, specifically the development of its Self-Service Data program from zero to more than 1,800 users that has paved the way for wider company change.
Despite the hype of machine learning and AI, not many businesses today have actually managed to bring transformational change through data, largely because they lack the most important pieces of the puzzle: transformation of people and processes through education. GE Aviation is an exception, having been able to develop their staff to leverage technology (including Dataiku) and enable employees’ ability to process, understand, and use data for day-to-day decisions. Since March 2017, the GE Aviation Self-Service Data program has seen the creation of more than 2,000 data products.
“We knew that we would never be able to hire enough data professionals to meet the data demands of the business, so instead, we decided to turn the business into data professionals,” said Jonathan Tudor, Senior Manager, Self-Service Data and Analytics at GE Aviation. “That’s how our Self-Service Data program was born, and now using Dataiku, employees across supply chain, engineering, and finance leverage the power of data to generate insights across their entire line of business — without having to receive hands-on direction from a data scientist or IT team.”
“GE is a 127-year-old company, and it takes a lot to innovate. Going from data silos to data democratization was no easy feat,” said Somesh Saxena [pictured], Product Owner of Dataiku and Alatian at GE Aviation. “But we were able to jumpstart our evolution to a data culture through a combination of technology - including partnering with Dataiku - plus processes and people, particularly through enablement and education. Gamification also played a critical role in getting the program off the ground, ensuring proper documentation and encouraging data quality. ” More...