Source: Shutterstock.com
Dataiku expands into Asia Pacific to support accelerating growth
DATAIKU Inc, the software developer behind the predictive analytics software platform Data Science Studio (DSS), has announced its plan to accelerate the expansion in the APAC region.
The move comes in support of an increased number of customers in the Asia Pacific, including Samsung and Hyundai Steel in Korea, as well as the adoption of academic licenses by top universities such as the National University of Singapore (NUS).
These customers, from Fortune 500s to SMEs, use Dataiku on a daily basis to create, build and run predictive applications that leverage data to address challenges and improve processes, sales and marketing functions.
From big enterprise to small startup, #DataScience at scale is hard (but not impossible!) | Words of wisdom from @fdouetteau: pic.twitter.com/l3sEUvxz06
— Dataiku (@dataiku) November 6, 2017
DSS, Dataiku’s flagship product, which provides end-to-end solutions for developing and deploying predictive analytics solutions, is at present experiencing accelerated adoption in Europe, US and Asia Pacific.
Dataiku has appointed veteran AI and data scientist Albert Antoine as its regional lead to aid the acceleration and expansion and support customers in Asia Pacific.
“Organizations in Asia Pacific are rapidly building up their complex data analyzing and relationship-predicting capabilities. With Antoine at the helm, I am confident that he and his team will provide excellent support to our current customers, while strengthening Dataiku’s presence and partnerships in this region,” said Florian Douetteau, CEO and co-founder of Dataiku.
With extensive experience in Asia Pacific after starting the operations of business optimization software leader ILOG and leading it for 17 years, Antoine is ready to lead Dataiku in the APAC region.
“I am privileged to work with Dataiku and Florian’s exceedingly brilliant team of researchers and technologists. The capabilities of Dataiku’s solutions will find tremendous traction in many organizations, especially in governments, critical infrastructures, utilities, tertiary institutions, software enterprises and so on,” he said.
Dataiku has developed significantly since it was founded in Europe in 2013. The start-up has grown into a global brand, driving innovation through cutting-edge data science and machine learning technologies.
Through the combination of these technologies and collaborative features, the Dataiku platform allows any person in an organization to contribute to the data science production process.
The platform – ‘Democratizing data science’ – enables each team member, from coders to analysts, to contribute to the data production and analysis process using the tools of which they have most knowledge. This collaborative approach creates meaningful analyses at a much quicker pace. What once took days, now takes only hours.
“Our driving philosophy at Dataiku is the idea that everyone should be able to contribute or gather insight from data science,” said Douetteau.
“Our driving philosophy at Dataiku is the idea that everyone should be able to contribute or gather insight from data science”. Source: Shutterstock.com
“We adhere to this because, in today’s world, we know that the most competitive data-driven organizations are the ones that make the most of all of their data, and the most effective way to do this is to empower people to use the tools they know best.”
“This is why we strive to deliver the best possible platform for collaboration that also combines the most advanced data science and machine learning technologies,” he added.
The company launched The Dataiku Academic Program in May this year, to provide free licensing, support and learning resources for teachers, researchers and students in the field of data science and business analytics.
“A vital part of helping everyone, everywhere, with their data analysis and data modeling skills is to provide free licenses of our software and specific support resources for academics, researchers, and personal learning to help the next generation of data scientists learn, create, and succeed.”