Systems | Development | Analytics | API | Testing

As a product leader, you're always looking for ways to stay ahead of the curve, meet evolving customer needs, and keep your product competitive. But with tight budgets, growing pressure to innovate, and constantly changing demands, it’s not always easy. Embedding AI-powered analytics into your application can be a powerful way to overcome these challenges and add more value for your users. But why is this approach so crucial, and how can you implement it effectively?

Using Business Intelligence (BI) tools can be overwhelming—especially for company executives, shopkeepers, or factory workers who may only engage with them occasionally. This challenge is one of the key reasons we set out to rethink how most users interact with their data. Rather than relying solely on interactive dashboards or static PDF reports, we're exploring more intuitive and user-guided approaches.

With the Snowflake Summit 2025 on the horizon, customers can anticipate groundbreaking innovations that address the challenges of leveraging data at scale and address. One of the greatest challenges is transforming raw data into AI, analytics, LMM, and RAG-ready formats. This requires effective ingestion, transformation, and governance. This is where Qlik, in collaboration with Snowflake, brings the heat.

Qlik Connect this year started a little differently. Not with slides. Not with a video. But with a few minutes of unified harmony. On stage stood the Barcelona Guitar Quartet — except instead of four guitars, there was only one. And yet the sound that emerged was rich, layered, and astonishing. If you had closed your eyes, you’d have sworn it was a full band. It was a masterclass in collaboration.

The future of data and analytics will be nothing like the experience we're used to today. We are at the beginning of a transformation that will fundamentally reshape how businesses use data, make decisions, and create value. At the center of this revolution is Agentic AI. Agentic AI fundamentally changes the way we work with data – moving from passive, reactive AI systems to autonomous, goal-oriented agents capable of reasoning, planning, and executing complex tasks across diverse data landscapes.

Open lakehouses powered by Apache Iceberg are redefining the landscape of data management. By bringing together the scalability of data lakes with the performance and reliability of data warehouses, lakehouses give you unprecedented flexibility and control over your data, while embracing open standards.

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.