Qlik announced a partnership with DataRobot to bring automated machine-learning modeling directly into Qlik, giving business users the power of predictive data decision-making within any analytics workflow. This integration greatly enhances a user’s ability to execute the entire range of data analysis – from historical and current state to future predictions – right within one Qlik instance. The partnership also builds on Qlik’s continued delivery of augmented intelligence and machine learning enhancements that give business users the ability to gain deeper insights from all their data.
“Machine learning is essential in helping users explore the vast arrays of data needed for unique insights that drive outcomes,” said Drew Clarke, SVP, Office of Strategy Management at Qlik. “The integration with DataRobot enhances Qlik’s existing AI and machine learning capabilities by bringing predictive modeling usually limited to data scientists to every business user.”
“We’re investing heavily in our data analytics performance to help democratize decision making across the business,” said Moto Thoda, Vice President of Information Services at Tokyo Century. “Working with innovative solutions like Qlik and DataRobot will help users make better decisions and more accurately predict where our best opportunities are, all through real-world data.”
Enterprises want to democratize data and enable users to make better data-driven decisions while leveraging artificial intelligence and machine learning. Qlik already delivers machine learning capabilities through its cognitive engine and platform with Insight Advisor, which auto-generates and suggests the best analytics and insights to explore based on the overall data set and a user’s search criteria. Now by leveraging Qlik’s open platform, extension technology and the open source Qlik DataRobot connector, DataRobot allows Qlik users to develop and democratize machine-learning models.
“Leading enterprises are embracing the need for AI and machine learning, and want help applying these innovations at scale across the business,” said Seann Gardiner, SVP of Business Development at DataRobot. “Automating data analysis and predictive machine learning driven models meets a need data scientists can’t scale to fill, and will enable business users to get more value and understanding from data not otherwise possible.”