Best Big Data Platforms for Qlik Application Automation

Compare the Top Big Data Platforms that integrate with Qlik Application Automation as of August 2025

This a list of Big Data platforms that integrate with Qlik Application Automation. Use the filters on the left to add additional filters for products that have integrations with Qlik Application Automation. View the products that work with Qlik Application Automation in the table below.

What are Big Data Platforms for Qlik Application Automation?

Big data platforms are systems that provide the infrastructure and tools needed to store, manage, process, and analyze large volumes of structured and unstructured data. These platforms typically offer scalable storage solutions, high-performance computing capabilities, and advanced analytics tools to help organizations extract insights from massive datasets. Big data platforms often support technologies such as distributed computing, machine learning, and real-time data processing, allowing businesses to leverage their data for decision-making, predictive analytics, and process optimization. By using these platforms, organizations can handle complex datasets efficiently, uncover hidden patterns, and drive data-driven innovation. Compare and read user reviews of the best Big Data platforms for Qlik Application Automation currently available using the table below. This list is updated regularly.

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    Qlik Sense
    Empower people at all skill levels to make data-driven decisions and take action when it matters most. Deeper interactivity. Broader context. Lightning fast. No one else compares. Qlik’s one-of-a-kind Associative technology brings unmatched power to the core of our industry-leading analytics experience. Empower all your users to explore freely at the speed of thought with hyperfast calculations, always in context, at scale. Yeah, it’s a big deal. And it’s why Qlik Sense takes you way beyond the limits of query-based analytics and dashboards our competitors offer. Insight Advisor in Qlik Sense uses AI to help your users understand and use data more effectively, minimizing cognitive bias, amplifying discovery, and elevating data literacy. Organizations need a dynamic relationship with information that reflects the current moment. Traditional, passive BI falls short.
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