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Everyone is taking part in the AI scramble, some more successfully than others, as we all know. But many enterprise companies are still just getting their feet wet. Here at Qlik we saw an opportunity to try to capture what it is that these successful companies did to get value from AI for their organizations. So, we partnered with IDC to get those answers and discovered that preparation is a major difference maker for success with AI.

At Qlik, we’ve always done things a little differently. Maybe it’s our Swedish heritage. Maybe it’s our relentless curiosity. But for us, “different” doesn’t just apply to our platform — with its unmatched breadth and flexibility — or our people, who bring world-class guidance and support to every customer and partner we work with. It’s a mindset that runs through everything we do, including how we approach our biggest event of the year: Qlik Connect.

Artificial Intelligence (AI) is no longer a futuristic ambition — it’s the strategic reality of today’s most competitive Independent Software Vendors (ISVs). In our recent Seamless Intelligence: Real-World AI Success Stories from Innovative ISVs webinar, I broke down how AI is transforming the ISV landscape, offering a blueprint for how organizations can move beyond dashboards, and into the age of predictive and generative intelligence.

Choosing the right storage format is crucial for optimizing performance, cost, and flexibility when working with cloud data. While file formats like Apache Parquet and Avro have been popular choices for storing data in data lakes, in recent years a new category called table formats has emerged to provide more management capabilities on top of these files. Among these, Apache Iceberg has been gaining significant adoption and momentum. So what exactly is Iceberg and why does it matter? Let’s dive in.

Happy Earth Day 2025! This year's theme, "Our Power, Our Planet," resonates deeply with Qlik's ongoing commitment to environmental stewardship. We believe that creating a sustainable future requires a collective effort, and we're dedicated to prioritizing and embracing renewable energy sources. Our goal is ambitious: to triple the use of clean energy sources by 2030.

Starting today, you might notice something different from us. A bold new look. A fresher voice. A clear message: Do Data Differently. It’s how we see the world, and how we want the world to see us. Because let’s face it: the pressure on businesses to move faster, cut through complexity, and act with confidence has never been higher.

As a design leader at Qlik, I have the privilege of working with an incredibly talented team of designers dedicated to creating thoughtful, intuitive, and impactful user experiences. We see design as more than aesthetics—it’s about problem-solving, innovation, and ensuring that every interaction adds value. Our mission is to craft experiences that are not just functional but also delightful, trustworthy, and consistent across our products.

One of the fastest-growing trends in the datasphere today is the development and use of data products. As we move deeper into 2025 and beyond, data product usage is going to explode. In fact, according to the Gartner 2024 Hype Cycle for Data Management, Data Products are currently at the Peak of Inflated Expectations, signaling strong interest and rapid evolution in this space. You can download the entire report here. The advantages and impact of this new paradigm extend beyond data engineers.

We know the role that AI can play in modern business, and the benefits it brings to employees and customers. But launching and sustaining a successful AI project remains a critical challenge for many organizations. Technology leaders across the globe are being tasked with using AI to drive business success, and it is becoming a vital pillar in reaching strategic goals.

Adopting AI? Risky. Not adopting AI? Riskier… It’s an interesting conundrum illustrating a broader truth: playing it safe is sometimes risky. To succeed, companies need to take smart risks—and those who do often achieve the greatest rewards. But a risk that is smart for one organization may not be as smart for another, so what risk is right for you?