Systems | Development | Analytics | API | Testing

The IDC MarketScape: Worldwide Data Integration Software Platform 2025 Vendor Assessment (doc, October 2025) notes, “Qlik delivers a comprehensive, cloud-agnostic data integration platform that spans real-time ingestion and replication, batch ETL/ELT, data quality, data productization, and governed self-service access for analytics and AI.” In the past, data integration was largely about moving information from A to B: ingestion, transformation, loading.

During London Tech Week, our CEO, Mike Capone, joined CNBC to talk about the UK’s position in the global AI landscape, and why this is a moment the country should not waste. His message was simple. The UK already has many of the ingredients for leadership in AI. The question now is how fast it can move from innovation to scale.

The enterprise AI landscape is transforming rapidly. On November 4th, Snowflake Intelligence—a breakthrough agentic AI platform built on the Cortex AI suite—ushers in a new era of business insights. With support for natural language querying (NLQ) and generation (NLG), organizations can interact with their data conversationally, unearthing real-time intelligence directly from complex, multimodal sources.

Accurate forecasting is one of the hardest problems for analytics teams. Demand shifts, supply chain constraints, and external factors like weather or pricing often interact in ways that simple models cannot capture. With the release of multivariate time series forecasting in Qlik Predict, business analysts can now model how multiple variables evolve together over time, directly inside Qlik Cloud, without writing code.

Apache Iceberg has rapidly become the leading open table format for modern data lakehouses, enabling organizations to combine the cost-effectiveness of data lakes with the reliability and performance of data warehouses. However, successfully implementing and managing Iceberg tables at enterprise scale requires understanding both the technical fundamentals and the operational complexities involved. This guide walks through the essentials of working with Iceberg tables, from creation to optimization.

Your teams don’t buy features; they buy outcomes. Speed to insight, trusted AI, lower TCO. That’s the lens for our Qlik Product Recap, a curated view of what’s new across Qlik and why it matters. We loved meeting many of you at Qlik Connect, and you’ll see several features we highlighted there plus everything we’ve shipped since, organized by the outcomes they enable. While Qlik Connect is a great moment to showcase innovation, it’s only one waypoint.

Real-time analytics has become a cornerstone of modern enterprises. Businesses are no longer satisfied with waiting hours or days for insights—they demand answers in seconds. The rise of AI, machine learning, and generative AI has only accelerated this need, putting immense pressure on data platforms to deliver reliable, scalable, and flexible architectures.

In Europe, trust is everything, and the bar is set by law. GDPR, the AI Act, NIS2, DORA, and the Data Act shape how data and AI must operate. Leaders need to show where data lives, who can touch it, and how it moves, and they want cloud speed and flexibility without giving up control, so sovereignty and transparency must be built in from day one.

In a special session at Qlik Connect this past May in Orlando, attendees got to hear from three industry leaders - Dave Freriks from Qlik, Randy Pettus from Snowflake, and Sathisan Vannadil from AWS - all coming together to detail a cutting-edge integration of generative AI across the three different platforms. Their mission: help oil and gas companies harness the power of advanced data solutions to manage complexity, drive efficiency, and accelerate decision-making.

Does it sometimes feel like the world of AI is constantly resetting the clock? One day you’re under pressure to deliver value fast with your AI project. The next, a prominent study claims most projects deliver zero value. Then, a leading business publication explains that, actually, value doesn’t even matter right now. All while the technology itself is advancing at a dizzying pace.