Systems | Development | Analytics | API | Testing

Earlier this year at Qlik Connect, we introduced Qlik Open Lakehouse, a fully managed, Apache Iceberg–based platform designed to make it easy and cost-effective for organizations to ingest, optimize, and manage data in open lakehouse architectures. And the first version of Qlik Open Lakehouse is generally available as of Sept 2025.

In 2023, the EU introduced measures to ensure there will be focus on the gender pay gap and at the same time strengthen employee rights, especially for companies that have more than 100 employees. For businesses and specifically HR Professionals, this directive coming into force in the mid-point of 2026 creates several challenges that require both operational and strategic responses.

Salesforce has now completed its acquisition of Informatica, in a deal positioned as a way to strengthen Salesforce’s AI data foundation. If you are an Informatica customer, that headline is not the end of the story. It is the start of a long, complicated chapter. Informatica is no longer an independent data company. It is now one piece of Salesforce’s AI CRM story. That has real consequences for your data strategy, your AI roadmap, and your room to manoeuvre.

In the AI era – the need for enterprise-wide data—from every operational system—available for instant analytics is real. Microsoft Fabric has fundamentally simplified the modern data estate, centering everything around the flexible, unified power of OneLake. A cornerstone of this platform is Mirroring, a low-latency, low-cost solution designed to break down silos. But for data engineering pioneers, the most exciting development is Open Mirroring.

As the demand for data to power AI models and real-time decision making continues to grow, organizations are increasingly looking for ways to simplify and optimize the ways to ingest, and process fresh data within the enterprise. On average, organizations allocate 20–50% of their annual data warehouse spend on compute for data ingestion, amounting to millions of dollars in costs for large enterprises.

In a previous blog post, we introduced one of the most significant advancements in Qlik Predict to date — multivariate time series (MVTS) forecasting, bringing enterprise-scale accuracy and context to complex prediction problems. But MVTS is only part of the story. Over the past few months, we’ve continued to enhance Qlik Predict with several powerful updates designed to make predictive AI more trustworthy, fair, and connected for our customers.

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.