Informatec strengthens its Data & AI expertise with Databricks With the Databricks Lakehouse Platform, Informatec unifies modern data engineering, BI, and AI capabilities to help companies accelerate innovation and create measurable business value.
Success Story SKAN AG With Informatec, SKAN AG stabilized its Power BI environment, modernized its ETL architecture, and established a future-proof, standardized BI organization.
Informatec strengthens its Data & AI expertise with Databricks With the Databricks Lakehouse Platform, Informatec unifies modern data engineering, BI, and AI capabilities to help companies accelerate innovation and create measurable business value.
Success Story SKAN AG With Informatec, SKAN AG stabilized its Power BI environment, modernized its ETL architecture, and established a future-proof, standardized BI organization.
Automatisation and democratisation of AI and machine learning in practice Advanced artificial intelligence technologies such as automated machine learning bring AI within reach for everyone. With these tools and technologies, organizations can put the power of machine learning in the hands of their technical specialists and data scientists. These advanced tools enable them to build machine learning models without writing a single line of code or having deep knowledge of algorithms.From BI to KI Live-Webinars Request a workshop FAQ Personal computers revolutionized industries by equipping people with tools that boosted creativity and productivity. The internet connected us globally, while smartphones and tablets made digital power ubiquitous. Today, artificial intelligence is driving the next wave of transformation — from automated analytics to generative AI that can create entirely new content.When people hear terms like AI or machine learning, many still think of highly complex processes and algorithms accessible only to experts. But modern no-code/low-code tools and AutoML platforms are opening the door for business teams as well. Identifying and implementing meaningful use cases no longer requires “rocket scientists.” Instead, teams across departments can ask: Which core challenges could AI help us solve more effectively? What data do we already have — or still need — to train intelligent models?As a result, far more employees can contribute their practical experience to influence strategic decisions and actively shape the future. From BI to AI-driven platforms How to Enrich Your BI Applications with AI and Machine Learning Capabilities Extending Business Intelligence solutions with AI and machine learning capabilities doesn’t have to be complicated.Through intelligent automation, the productivity of data scientists can be significantly increased—while business users are more likely to adopt new approaches when AI functions are seamlessly integrated into existing BI software such as Qlik, Tableau, or Power BI. Modern AutoML and no-code platforms enable users to deepen their analytics without having to be experts in machine learning. BI and AI – A Powerful Combination In today’s era of exploding data volumes, traditional BI techniques alone are no longer enough to fully leverage available information and drive the best business decisions. Organizations that incorporate machine learning (ML) and artificial intelligence (AI) can uncover actionable insights that solve real business challenges—from predictive analytics and automated decision-making to generative AI applications.However, many business users lack the time or interest to develop deep data science skills. This is where AutoML solutions and AI-enabled BI platforms come in: they democratize data science, lower the barriers to entry, and deliver results that can be applied directly in business contexts.Benefits, Fundamentals, and Best PracticesAutomated machine learning complements human expertise rather than replacing it—business knowledge and AI work hand in hand.Quick-win projects deliver fast, measurable ROI and help build trust in the technology.Self-service analytics with AI support makes it easier for business teams to experiment with data and identify new use cases.Integration with existing BI systems ensures a smooth extension—users stay in their familiar environment while still benefiting from AI.This way, executives, analysts, and business professionals can build, test, and deploy high-quality machine learning models without deep programming knowledge. The result: better decisions, greater efficiency, and a BI landscape fully ready for the age of AI. Artificial Intelligence (AI) Artificial intelligence (AI) Drives the Logical Development of Business Intelligence (BI) With AI-powered BI, organizations can generate real-time insights, ensure continuous access to up-to-date data, and automatically uncover complex patterns. This enables businesses to make fast, well-founded, and strategic decisions despite the rapid growth of data volumes.Modern BI tools now offer far more than dashboards. They provide predictive analytics, generative AI-driven insights, and conversational analytics that directly support managers and business units in their decision-making. In this way, business intelligence evolves from a pure reporting tool into an intelligent decision-making platform that actively shapes corporate strategy.Discover more about Artificial intelligence Machine Learning (ML) The Next Level of Intelligent Business Intelligence With machine learning, BI applications can become even more powerful. Models automatically detect patterns, predictions become more accurate, and complex relationships can be directly incorporated into decision-making. This enables organizations to make fast, well-informed, and strategic decisions even as data volumes continue to grow.Modern ML platforms offer not only automated analyses but also predictive analytics, generative AI-driven insights, and self-service capabilities that directly support business units. In this way, business intelligence evolves into an intelligent decision-making platform that actively drives corporate strategy.Discover more about Machine Learning Our Webinar-Series Artificial Intelligence & Automated Machine Learning – VIRTUAL DATEDiscover practical, industry-specific use cases in our webinar series that showcase the successful application of AI and ML technologies within Qlik environments. Learn how to train models effectively to deliver accurate predictions, identify patterns, and support data-driven decision-making. #predictionisnow WEBINAR Qlik AutoML - No Coding RequiredIn our Live-Webinar (19.06.2025 14h00 - 14h30) you will learn how to use Qlik AutoML to easily make data-driven predictions and seamlessly integrate them directly into your analyses. to webinar recording WEBINAR Qlik Cloud Data IntegrationIn our Live-Webinar (20.06.2024 14h00 - 14h30) you will learn how to transfer data from multiple sources into your desired target infrastruture in real time, without putting any strain on the source systems.to webinar recording FAQ What sets automated Machine Learning (AutoML) apart from traditional Machine Learning? In traditional ML, data scientists manually design models and optimize parameters step by step. AutoML automates many of these tasks – from data preprocessing and feature engineering to model validation – enabling the development of high-quality models even without deep expert knowledge. What role does Generative AI play in Business Intelligence? While traditional BI focuses primarily on reporting and analysis, Generative AI can automatically create content such as text, forecasts, or visualizations. This expands BI to new forms of interaction, for example through conversational analytics, where users can ask questions in natural language and receive immediate answers. What governance aspects need to be considered in democratized AI? As more employees gain access to AI-powered tools, the importance of data quality, privacy, and ethical guidelines increases. Organizations should define clear rules and responsibilities to prevent incorrect or biased outcomes.