Visual drag-and-drop tools reduce dependency on scripting, streamlining data preparation for analytics and AI
Qlik, a global leader in data integration, data quality, analytics, and artificial intelligence, has announced the launch of its innovative Data Flow capabilities within Qlik Cloud Analytics™. This new feature is designed to simplify the traditionally time-consuming process of preparing datasets for analytics and artificial intelligence (AI) applications. With a visually intuitive drag-and-drop interface, users can now effortlessly combine, clean, and shape data without relying on complex technical scripting. This no-code approach to data preparation opens up analytics to a broader range of users, both technical and non-technical, enabling faster creation of high-quality, AI-ready datasets.
The Data Flow feature offers a visual and flexible method for data preparation, addressing key challenges such as lengthy processes and skill gaps. Key highlights include:
- Drag-and-Drop Simplicity: Users can combine, clean, and transform multiple datasets using an intuitive visual interface, eliminating the need for coding.
- Transparency and Trust: Every action performed within the tool automatically generates Qlik script, allowing users to track and understand their data preparation process, building confidence in the results.
- Flexible Workflows: The tool supports no-code, low-code, and pro-code approaches, enabling users to adjust their workflows according to their technical expertise and project requirements.
- End-to-End Integration: Seamlessly integrated with Qlik Cloud Analytics, Data Flow ensures smooth transitions from data preparation to AI implementation and data visualizations.
By drastically reducing the time spent on data preparation, Data Flow enables users to shift focus to generating valuable insights and driving data-informed decisions.
“Efficient data preparation has always been a critical, yet time-consuming, part of our analytics process,” said Jon Carpenter, Systems and Programming Manager at Pima County. “We’re excited to see how Data Flow can help us accelerate insights and make more informed decisions.”
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Data preparation is often the most time-intensive aspect of analytics projects, leading to bottlenecks and hindering effective data usage. Data Flow resolves this challenge by giving users, regardless of their technical expertise, full control over their data workflows.
This new innovation reflects a growing demand across industries to democratize access to analytics and AI capabilities. By enabling a wider variety of users to prepare AI-ready, high-quality data, Qlik is helping businesses reduce dependence on IT teams, improve time-to-insight, and maintain data accuracy and consistency.
“Data Flow is the type of innovation we’ve been looking for—enabling teams across our organization to quickly and easily create high-quality datasets without needing deep technical expertise,” said Angel Monjarás, Qlik Platform Manager at C40 Cities.
As part of its ongoing commitment to simplifying analytics and bridging the gap between IT and business users, Qlik’s Data Flow integrates the powerful capabilities of Qlik Talend Cloud with Qlik Cloud Analytics. This integration ensures users have seamless access to high-quality, trusted data, ultimately driving better business outcomes.
“Data preparation is often an overlooked yet essential step in the analytics and AI process,” said Brendan Grady, Executive Vice President and General Manager of Qlik’s Analytics Business Unit. “With Data Flow, we’re enabling a broader range of users to confidently prepare AI-ready datasets without requiring technical expertise. This innovation removes traditional barriers and accelerates the journey from raw data to actionable insights, helping organizations drive value faster and more effectively.”
Data Flow is now available to all Qlik Cloud Analytics customers. This feature provides an accessible, user-friendly solution for preparing high-quality datasets, streamlining the data-to-decision process and helping organizations remain competitive in an increasingly data-driven world.