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Kalman Tiboldi - CTO & Founder at GemOne-TVH - Simplify or Die: Why Complexity Is the Real IT Challenge
Germany Sep 29, 2025 Country Members Virtual german
Unsere Wissensaustausch-Briefings "AI & Data Knowledge Transfer" zielen darauf ab, CIDOs und Senior Digital Leaders mit praktischen Anwendungen und umsetzbaren Erkenntnissen von Fachexperten zu vermitteln, die den Weg für transformative digitale Reisen ebnen.
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Germany Sep 30, 2025 Country Members Physical german
Von der Theorie in die Praxis: Erst Business, dann Bier.Unstrukturierte Daten sind das verborgene Kapital vieler Unternehmen – und zugleich eine der größten Herausforderungen moderner IT. Gemeinsam mit CIOs, CDOs und CTOs der CIONET-Community sprechen wir zuerst bei WeWork München über Strategien, Technologien und echte Use Cases, um dieses Potenzial zu heben. Danach geht's weiter auf die Wiesn – für den offenen Austausch in bayerischer Atmosphäre.
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UK Sep 30, 2025 Invitation Only Physical english
This exclusive Jefferson dinner, hosted by Mendix and CIONET, brings together a hand-picked group of senior executives and digital leaders from across the UK financial sector.
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Netherlands Sep 30, 2025 Invitation Only Physical dutch
Alleen op uitnodiging. Mastering Digital Sovereignty Control, trust and resilience in an era of geopolitical and regulatory shifts. From the Network to the Data.
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Belgium Oct 1, 2025 Invitation Only Physical english
In today’s rapidly evolving technological landscape, organisations face a critical challenge: how to modernise their legacy systems while managing costs, maintaining security, and ensuring operational continuity. This exclusive round table discussion brings together CIOs, CTOs, and Digital Leaders to explore best practices for legacy and lifecycle management. Key topics include extending the lifespan of existing systems, mitigating cyber security risks, optimising costs, and integrating legacy platforms with modern technologies. We’ll also delve into sustainability, workforce challenges, and future-proofing IT infrastructures to navigate technological obsolescence.
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Germany Oct 7, 2025 Country Members Virtual german
Alle nutzen KI, aber keiner weiß wie effektiv! Im Jahr 2025 sind wir als IT-EntscheiderInnen gefordert die Wünsche der Fachbereiche an Künstliche Intelligenz zu managen. Welche KI dient als Copilot für unsere Mitarbeitenden, inwieweit hat diese Zugang zu Firmenwissen und könnten wir heute bereits sinnvoll einen KI Agenten in die IT Systemlandschaft einbinden? Unser Business Partner Scheer PAS spricht als Anbieter einer Process iPaaS Plattform mit hunderten Unternehmen jedes Jahr über IT-Integration. In dieser Online-Session besprechen wir erste Reifegradmodelle zu KI, wo der deutsche Mittelstand sich befindet und wie wir die nächste Innovationsstufe erreichen. Wir teilen praktische Erfahrungen aus dem Marktumfeld und planen unsere nächsten Schritte in der Adaption von KI.
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Isabel Group automates operations, takes efficiency to the next level with Azure data platform
Belgian FinTech Isabel Group revamps platform with Azure for data & automation. New platform unlocks flexibility, unstructured data handling & machine learning, empowering employees & clients.
Our analysis of the cloud computing market revealed Azure as a leader in data analytics. - Michael Van de Borne: Data Analytics Manager - Isabel Group
For Isabel Group, simplification is a key to success. The Belgium-based fintech company’s core mission is removing hassle for customers through IT-based products that facilitate the exchange of documents, identities, and payments. In the complex world of financial administration, Isabel Group finds ways to streamline processes for its customers.
It was a natural evolution to enter into the wider Microsoft ecosystem both from a business continuity perspective and to ease the migration effort. - Michael Van de Borne: Data Analytics Manager - Isabel Group
Isabel Group originally had an on-premises data platform that was used only for BI purposes. The BI platform was a traditional SQL server-based data warehouse with SQL Server Integration Services (SSIS), SQL Server Analysis Services, and SQL Server Reporting Services. Employees accessed data through multidimensional models and paginated reports. For reporting requests, business users were required to file a ticket and a BI developer would query the data warehouse.
The platform’s single-purpose construction meant that it couldn’t handle unstructured data or be utilized to support other critical business processes. Many operations did not use automation, resulting in repetitious, error-prone tasks that needed to be carried out manually. Because the solution used on-premises infrastructure, business users were forced to rely on database administrators and datacenter operators for managing physical upgrades, hindering their autonomy. The lack of flexibility prevented internal business users from improving processes like marketing campaigns and billing and forced business decision makers to use inefficient tools to compensate for what the BI platform didn’t provide. “Or worse, they went without the proper data or no data at all,” says Van de Borne.
Isabel Group had an opportunity to simplify its own process—and unlock new business capabilities at the same time. The company needed a mature, scalable platform that could make use of machine learning and advanced analytics while offering seamless integration through every step of the data pipeline.
Azure machine learning and data science can address all kinds of problems that nobody believed we could solve previously. - Michael Van de Borne: Data Analytics Manager - Isabel Group
Going from an on-premises Microsoft SQL Server setup—where internal users worked on Windows laptops with Microsoft Office products—to an Azure ecosystem made sense. “It was a natural evolution to integrate into the wider Microsoft ecosystem both from a business continuity perspective and to ease the migration effort,” says Van de Borne. “Our analysis of the cloud computing market revealed Azure as a leader in data analytics.” Isabel Group also took advantage of Fast Track Support from Microsoft, which offered a series of workshops to evaluate how different Azure services could be used.
Working with Microsoft Cloud Partner Program member element61, Isabel Group built a solution using Microsoft Azure Data Factory with self-hosted integration runtimes, Azure Data Lake Storage for scaling and storage, Azure Databricks for processing large datasets, and Microsoft Power BI Premium for insights and reporting. Isabel Group used Azure DevOps to build a custom toolchain, build and deploy models and reports to Power BI, and test and deploy data engineering code to Databricks.
The process starts with raw data that is taken from databases via integration runtimes or sent by apps, then raw data is sent to the staging area in Azure Data Factory. Data is arranged in star schema and business keys and foreign keys are updated through Databricks, then Databricks triggers Power BI API to refresh datasets. With datasets refreshed, business insights are ready to be presented. The end-to-end process includes machine learning model training, a feature that Isabel Group wanted but was unable to fit into their old system.
The process was a complete redevelopment of all the SSIS pipelines Isabel Group used—which number in the hundreds. After two and a half years of planning, problem-solving, and building custom tools and libraries, Isabel Group was able to fully decommission its on-premises BI platform and switch over to Azure.
With the move from traditional BI reporting to more comprehensive data engineering and analysis, Isabel Group gained the ability to process larger and unstructured datasets. Plus, the automation possibilities are a huge win for the team. Infrastructure and data pipelines are automated in the new solution—in fact, the team even automated the creation of new data pipelines, since so many needed to be migrated or remade. “This has unlocked a new range of possibilities,” says Van de Borne. “Alerts, in the case of a failure, and data quality tests are now automated.”
With the modern platform, the data team can provide new data initiatives more quickly and data engineers are more efficient. This means less time is needed to maintain pipelines and reports, and more time can be given to onboarding new use cases. For example, Van de Borne’s team has already begun work on new products used for validating the identity of payment beneficiaries in real time for help with fraud detection. As a result, employees have increased trust in the data team and platform, and Isabel Group can offer new services that continue to streamline and simplify business for its customers.
With the recently deployed platform, Isabel Group expects faster turnaround times for the creation of data products and machine learning-based solutions for both internal and external use. Employees are excited to explore advanced analytics and long-term, organization-wide data governance models. Insights into user usage patterns across product offerings will help steer future development of product features and identify cross-selling opportunities within its customer base. “Azure machine learning and data science can address all kinds of problems that nobody believed we could solve previously,” says Van de Borne.
Kalman Tiboldi - CTO & Founder at GemOne-TVH - Simplify or Die: Why Complexity Is the Real IT Challenge
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Isabelle Droll - CIO for Airline, Corporate, Hotels & Resorts and Sustainability at TUI - Data, Diversity, and Destinations
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Sharon Prior - CIO in transition - How Great Tech Leadership Begins with Business Thinking
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José Antonio López, Group CIO at TOUS - Jewels, Data & AI: Inside the Digital Transformation of TOUS
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Tom Tanghe - General Manager ITC EMEA at Daikin Europe - Reinventing the CIO Role
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CIOFEST 2025 - From Order Taker to Proactive Disruptor
As AI transitions from a specialised tool to an all-pervasive force, understanding its profound implications for our human lives is no longer merely academic but an urgent imperative for social well-being and strategic preparedness.
Geopolitical tensions have dominated the headlines for over two years now. In this context, the cyber threat landscape is also evolving rapidly. The protection and security of critical infrastructure – both physical and digital – is becoming increasingly important.
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