Direct Integration Makes It Easy for Business Users to Go from Data Analysis to Predictive Decisions with Automated Machine Learning Models
Philadelphia, Pennsylvania - Qlik today 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.”
The Qlik open source extension and connector enables:
This seamless integration enables predictive modeling and remodeling within one interface, ensuring the user gets the best model possible for their analysis.
Qlik and DataRobot will be showcasing these enhanced capabilities at the upcoming Financial Services Analytics Summit in New York on March 7th, where DataRobot is a Platinum Sponsor. For more information and to register visit: http://go.qlik.com/2019-FinServSummit.html.
For additional information, video walkthrough, documentation and download of the integration between Qlik and DataRobot visit http://bit.ly/QlikDataRobot.
DataRobot is the category creator and leading provider of automated machine learning. Organizations worldwide use DataRobot to empower the teams they already have in place to rapidly build and deploy machine learning models and create advanced AI applications. With a library of hundreds of the most powerful open source machine learning algorithms, the DataRobot platform encapsulates every best practice and safeguard to accelerate and scale data science capabilities while maximizing transparency, accuracy and collaboration.
By making data scientists more productive and enabling the democratization of data science, DataRobot helps organizations transform into AI-driven enterprises. With offices around the globe, DataRobot is backed by $225 million in funding from top-tier firms, including New Enterprise Associates, Sapphire Ventures, Meritech and DFJ. For more information, visit www.datarobot.com, and join the conversation on Twitter and LinkedIn.