Covering Disruptive Technology Powering Business in The Digital Age

Dataiku, the world’s most advanced Enterprise AI platform, announced the launch of Dataiku Online, which makes their AI and machine learning platform available as an online service for smaller, more agile organisations. Dataiku Online is fully managed by Dataiku, which allows companies of any size to access the full power of its platform without added pressure on IT to install and manage resources.

Dataiku Online provides everything a company needs to build powerful analytics projects, with data preparation, data visualisation, AutoML, reporting, and dashboards all in one place. It has all of the key capabilities as Dataiku’s flagship product, with a few configurations and design tweaks to match its managed usage – and without the IT resources required to manage an enterprise-scale deployment. The flexible interface enables collaboration across a broad range of business and data team users. With Dataiku Online, any team can start their data journey within minutes, connect to their data sources easily, and start deploying projects in days, and they can do so at a price point that makes sense for their current stage of growth.

“Accessibility has always been of the utmost importance at Dataiku. We developed Dataiku Online to address the needs of small and midsize businesses, in addition to startups,” said Dataiku CEO Florian Douetteau. “We want to help companies that are just beginning their data and analytics journey to access the full power of our platform, where they can start by enhancing their day-to-day operations with simple data tools and then take their data even further with machine learning. Companies don’t need big data to do big things with their data, and Dataiku Online will make it easier for a whole new class of companies — from lean startups to scaling SMBs — to start.”

While enterprise organisations can invest in large data storage and data management solutions, that level of investment is often out of reach for smaller organisations. These companies still need analytics and AI to generate insights and drive value for their business. With Dataiku Online, businesses can take advantage of a modern, cloud data stack and data storage tools from Snowflake, Google Big Query, Amazon Redshift, and more. There is even a pre-integrated version of Dataiku Online available through the Snowflake Marketplace.

Since rolling out the service in a private beta earlier this year, a small handful of customers have been using Dataiku Online to connect to cloud data warehouses, prepare data, and build analytics and AI projects. They’ve found that it quickly enables teams to work with a variety of data sources, ultimately driving analytics and predictive models to production much faster than with other tools.

“Dataiku Online allows us to focus on analysis, not server administration. The customer service is fast as well. Data insights fuel our growth, and Dataiku Online enables us to develop insights faster than our competitors,” said Scott Walker, Managing Partner at Sarissa Partners.

To complement the accessibility of Dataiku Online for startups and SMBs, and as part of the ongoing effort to democratise the use of data, Dataiku is also launching an offering specifically for startups, designed to help early-stage companies take advantage of all their data in one platform and begin their analytics journey. Seed-stage companies — those less than two years old, or with USD5M or less in funding — and startups founded less than five years ago or with less than USD10M in funding can be eligible for discounted pricing specific to their current stage of growth.

Dataiku was founded in 2013 with the mission to democratise access to data insights for real people and enable companies to build their own path towards AI. The company has grown exponentially since, now serving hundreds of customers across the globe including Schlumberger, GE Aviation, Sephora, Unilever, BNP Paribas, Premera Blue Cross and Kuka. from offices in New York, Paris, London, Munich, Sydney and Singapore.

(0)(0)