Systems | Development | Analytics | API | Testing

Benchmarking Ingestion Costs and Performance of Qlik Open Lakehouse Vs a Data Warehouse

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.

Access and Prepare Your Data

Join Mike Tarallo live this Friday, November 14th at 10AM ET as he explores the many ways to access and prepare your data in Qlik Cloud. Whether you’re loading from the Data Load Editor with Qlik script, working with registered datasets in the Data Catalog, or streamlining your data prep with Table Recipes, Data Flows, or the Data Manager — this session will help you understand when and why to use each approach.

Smarter, Fairer, and More Transparent AI in Qlik Predict

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.

Beyond Pipelines: Building the Trust Layer for AI

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.

The UK's AI Moment: From Innovation to Scale

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.

Managing Risk in Banking and Capital Markets with Qlik and Databricks

Discover how Qlik and Databricks are transforming risk management for banks and capital markets Learn how leading financial institutions are leveraging data and AI to manage risk, prevent fraud, and stay ahead of industry regulations. Learn how modernizing your data estate and harnessing the power of artificial intelligence can streamline compliance and automate complex processes. Get a sneak peek at the tools and strategies that help banks get AI-ready, integrate data pipelines, and unlock the benefits of generative AI.

Unlocking Enterprise AI: How Qlik and Snowflake Intelligence Empower Data-Driven Decisions

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.

Forecast Smarter with Multivariate Time Series in Qlik Predict

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.