CDAO Nordics 2025 schedule

This panel explores how enterprises can align AI, digital transformation, and data strategy into a unified engine of business growth and resilience. 

• Rethinking the role of data in a platform-led enterprise 

• Breaking down silos to drive cross-functional collaboration and shared KPIs 

• Ensuring responsible and explainable use of AI in complex environments 

• Enabling real-time, insight-led decision-making at all levels 

• Creating a scalable, data-driven culture in legacy-rich industries 

Luba Weissmann, AI & Data Director – EPIROC 

Henrik Tingwall, Head of Lean PMO and Digital – APOTEKET 

Sheik Atiqul Alam, Data and Insight Manager – ARLA FOODS 

• Why mainframes still matter in today’s digital and AI landscape
• The role of AI in accelerating legacy system rationalization
• How to unify data and business logic across legacy and modern systems
• Understanding the limits of AI when dealing with complex enterprise infrastructure
• Lessons learned from real-world mainframe transformation projects 

Retail and consumer leaders will explore how they’re applying AI and GenAI to optimize customer experience, supply chains, and marketing. 

• Creating personalized shopping experiences at scale 

• Predicting demand and optimizing supply chains in real time 

• Chatbots, virtual assistants, and AI-enhanced customer service 

• Leveraging GenAI for marketing content and campaign strategy 

• Ethical and privacy-conscious personalization in Nordic markets 

Moderator: Rakesh Rana, PhD, Head of Data – HAYPP GROUP 

Roundtable: Driving Business Agility with Data-Driven Decision-Making 

This session explores how organizations are empowering business units to make informed, agile decisions by embedding data across all workflows. 

• Aligning data with shifting business priorities in uncertain times 

• Creating fast feedback loops between insight and action 

• Making data accessible to decision-makers beyond the data team 

• Enabling line-of-business leaders with guided analytics 

• Identifying and scaling “quick-win” use cases 

Erica Campbell, Global Consumer Data & Advanced Analytics Director – Electrolux 

Sheik Atiqul Alam, Data and Insight Manager – ARLA FOODS 

Join this peer-led group to discuss the critical elements of building future-ready, reliable, and flexible data infrastructure.  

Building the backbone for real-time, reliable, and cost-efficient data operations 

• Architecting for low-latency, high-throughput analytics pipelines 

• Ensuring data quality, governance, and lineage in multi-source environments 

• Migrating from monolithic to modular, cloud-optimized data platforms 

• Managing hybrid/multi-cloud data storage while controlling cost and compliance 

• Leveraging streaming data where it matters: operational analytics & ML enablement 

Explore how enterprises are transitioning to domain-driven, decentralized data architecture models while maintaining alignment and governance. 

• Implementing domain-oriented ownership of data products 

• Overcoming cultural barriers in adopting a federated model 

• Aligning data mesh with legacy systems and cloud migrations 

• Setting standards for interoperability and discoverability 

• Lessons from pilot programs: metrics, adoption, and resistance 

To drive consistent business impact, data teams need more than just a modern stack — they need a clear, structured operating system. In this session, Pier Martin will explore how embedding human-centered principles and soft skills into your data culture can radically improve ROI. From real-world day-to-day team challenges to practical leadership strategies, he’ll offer insights and immediate actions for building stronger, more effective data functions. 

• Data Teams Need an Operating System—Not Just a Stack: Why focusing only on tools and technology misses the mark, and how process, mindset, and communication routines create consistency across data functions. 

• Soft Skills as a Multiplier for ROI: How skills like storytelling, empathy, and influence-building amplify technical output and help data teams embed more deeply into business strategy. 

• Prioritization as a Leadership Capability: Why leaving prioritization to tooling or backlog grooming is a mistake—and how data leaders can guide their teams by aligning decisions to business impact. 

• From Insight to Action: Common roadblocks data teams face and practical changes leaders can implement immediately to improve alignment, output, and morale. 

• About Pirkanmaa Wellbeing Services County: Serving over half a million citizens with health, social, and rescue services, supported by 20,000 employees. 

• Data at the Core: These services generate vast and diverse data that, when managed effectively, can unlock real value for both operations and citizens. 

• Enabling Data-Driven Operations: Success requires addressing the full chain — from data collection to refinement, governance, and meaningful utilization. 

• Knowledge Management in Action: Practical examples and approaches for turning raw service data into actionable insights that improve decision-making, efficiency, and service quality. 

• What leaders must do now to future-proof AI and analytics teams 

• Embedding risk management into AI-driven transformation 

• Striking the balance between innovation and accountability 

• Managing AI risks and compliance in highly regulated industries 

• Building governance frameworks that enable innovation without losing control 

• How evolving regulation impacts the structure and role of data/AI teams 

Ashish Soni, Head of Data Science & Analytics, Financial Crime Prevention – SEB 

• Initial scepticism and what changed your mind on Data Governance lead role 

• The hiring process and role definition for the data governance lead  

• Concrete examples of how this integration improved organizational awareness  

• The cohesive relationship between data, architecture, and business outcomes  

• Key lessons learned and recommendations for other organizations Challenges faced and how you overcame them 

Building a Centralized Data Lakehouse in the Cloud at NOBA Bank Group 

• Our Merger Challenge: Integrating and harmonizing data assets from two organizations. 

• Why the Cloud: Drivers for moving to a scalable, secure, and flexible cloud-first architecture. 

• Centralized Data Lakehouse Approach: Balancing structure (data warehouse) with flexibility (data lake) to meet diverse business needs. 

• Moving to the cloud to unify and modernize the data foundation. 

• Ensuring quality, governance, and scalability in the process. 

• Preparing the groundwork for advanced analytics and AI. 

Description: 
As GenAI becomes embedded across organizations, it’s redefining how data is owned, accessed, and acted upon. This roundtable brings together data and AI leaders from across sectors to discuss how to balance innovation with accountability, ensure ethical ownership of insights, and futureproof governance structures. 

Discussion Points: 

• Who owns the value created by GenAI? Business, tech, or the customer? 

• How is GenAI shifting the role of the CDO, CIO, and business leaders? 

• Empowering product and domain teams to responsibly use LLMs 

• The rise of internal data marketplaces — trend or transformation? 

• How to avoid decentralisation chaos: platform strategy, trust, and standards 

Ramakrishna Poojari, Head of Group Data Strategy and Data Transformation Office – SWEDBANK 

Luba Weissmann, AI & Data Director – EPIROC 

Reza Abedi, Lead Data Governance – FORTUM