CDAO Germany schedule

During this 10-minute networking session, the aim of the game is to go and meet two people you don't already know.  Have fun! 

In a world driven by data, the way organizations manage and structure their information can make or break their success. Discover why mastering data management isn’t just a technical necessity—but the key to unlocking scalable, business-transforming AI 

• Unlocking New Revenue Streams: Explore how data partnerships can identify untapped markets and customer segments, driving new business opportunities. 

• Enhancing Decision-Making: Demonstrate how collaborative data analytics improves accuracy and speed in strategic decision-making, leading to better business outcomes. 

• Innovative Solutions and Services: Highlight the development of new products and services through shared data insights, fostering innovation and competitive advantage. 

Data management is evolving, shaped by the decentralisation of data ownership, increasing demands for high-quality data, and the growing role of AI in driving insights and innovation. Traditional, centralised approaches often fall short in meeting organisational needs for speed, accessibility, and scalable data solutions. At the heart of this transformation lies the concept of data contracts—a practical and effective method for managing data with precision and agility, while ensuring it is fit for both operational use and AI-driven applications. 

Join Coursera for an insightful session with Charlotte Evans, Director of Global Customer Advocacy, where she will explore the transformation towards skills-based organizations and how to infuse skills into talent management for your data and technical teams. Charlotte will share how some of the world's best learning teams are working with their business leaders on skill development, including measurement frameworks, skills taxonomies, and culture change. She will then offer specific recommendations for how you can help your organization further its objectives by becoming skills based. Don't miss this opportunity to gain valuable insights and strategies to empower your organization's talent development initiatives. 

Operational clarity is the key to cutting through noise, aligning teams, and making confident decisions. This talk dives into the role of metric trees, business reviews (WBRs), and data-driven root cause analysis in building a shared understanding of business performance. We'll cover how to identify controllable input metrics, use exception-based reporting (XMR charts), and avoid dashboard overload—all to ensure decisions are based on knowledge, not opinions. Expect actionable insights on structuring reviews, fostering accountability, and transforming data into a true driver of business success

In this presentation, I’ll explore our journey in establishing and implementing a robust data strategy. We’ll delve into the key components of our approach: 

• Strategy Formulation: How we developed our data strategy to align with business objectives. 

• Team Structure: Our focus on building a team centered on enablement and strategy execution. 

• Program Management: The critical role of program management in orchestrating our data initiatives. 

• Data Mesh Implementation: Our experiences, successes, and lessons learned in transitioning the company to a data mesh. 

• Enablement Framework: How we created a support structure to empower teams across the company with self-service analytics. 

• Metrics and Success Indicators: Key performance indicators we use to measure progress and success. 

• Challenges and Solutions: Honest insights into the obstacles we faced and how we overcame them. 

• Future Outlook: Our vision for the continued evolution of our data strategy. 

With the advent of cloud computing and (Gen)AI, the breaking point of most use cases is not computational power or modelling accuracy, but the data which is used as basis for predictions. Data Accessibility and Quality are starting points, but beyond that, there is more that you need to ensure to unlock powerful insights. In this talk, I will discuss some of the learnings running analytics for a global line of business, where hands- on problems meet strategy execution at scale, with a particular focus on how different teams need to work together to realize an AI vision. 

Agentic AI is undoubtedly one of today's hottest topics, yet practical examples of its real-world impact on enterprise operations remain scarce. In this insightful session, Mark Zakhvatkin will share concrete examples of how IU International University of Applied Sciences leverages agentic AI to enhance product development and streamline internal processes. Mark will also discuss scenarios where an agentic approach proved less effective, highlighting the current boundaries of its applicability. Join this engaging talk to discover valuable lessons and actionable insights from IU's experience that can be directly applied to your own organization! 

• Why is it essential to build a reliable data foundation? 

• What is required to achieve a reliable data foundation? 

• How can traditional organizations overcome the inertia of legacy systems to become data driven? 

• What role do leadership and culture play in driving long-term data success? 

Andrew Spires, EMEA Data Integrity Lead – TRICENTIS 

Olga Ivina, Global Head of Data Science Engineering – MICROSOFT 

Dr. Andreas Hamprecht, CIO/CDO – DEUTSCHE BAHN 

• DA Team Success Factors 

• Competency Development 

• Working with Principles 

What You’ll Learn: 

• AI Regulatory Landscape: Key regulations and their impact on businesses. 

• Compliance Strategies: Effective ways to ensure your AI initiatives meet regulatory standards. 

• Opportunities in Compliance: Leveraging regulations for innovation and competitive advantage. 

• Implementation Tips: Practical advice for integrating compliant AI solutions. 

Workshop Outline: 

1. Introduction: Overview of AI regulations and their significance. 

1. Regulatory Landscape: Key regulations and their implications. 

1. Compliance Strategies: Practical approaches and shared experiences. 

1. Opportunities in Regulation: How compliance can drive innovation. 

1. Implementation Tips: Best practices for compliant AI solutions. 

How You Can Participate: 

• No preparation needed! 

• Share your experiences and insights. 

• Join discussions and ask questions. 

• Consider regulatory opportunities for your industry. 

Aleksejs Plotnikovs, Founder of chiefdata.ai, and former Lead of Data & AI Strategy at Microsoft 

Alexander Woellwarth-Lauterburg, Vice President of AI - Rhapsody Media Group 

 The wind industry is on its fast way to higher automation via AI and better decision making due to market demands. Ten years ago, planning and optimizing a wind farm with many wind turbines was a rather manual task with long lead times. Today it is possible within minutes. This talk focuses on the enormous rate of change within processes as well as costs and highlights explicitly the cultural mindset change in this former traditional industry. 

• How do we identify the most relevant metrics that align with our business objectives? 

• What best practices can we use to ensure our metrics are actionable and drive decision-making? 

• How can we effectively communicate the importance and impact of these metrics to stakeholders? 

• What are common pitfalls in metric creation and how can we avoid them to ensure data accuracy and relevance? 

Pier Martin, Vice President, Data and Analytics - ZEAL Network SE  

Marcin Nizinski, Head of IT Audit and Data Analytics in Assurance – SIEMENS ENERGY 

Jesse Rothenberg, Head of Data & Insights Unit – ABLETON 

Maximilian Ehrlich, Director Data & Insights – TONIES 

Michael Brüdgam, Head of Division Center of Excellence- ENERCON 

• How can organizations ensure their data strategy is effectively aligned with their overall business objectives? 

• What are the common pitfalls organizations face when their data strategy does not align with their business strategy, and how can these be avoided? 

• What role does data governance play in aligning data strategy with business goals, and what are the best practices for implementing it? 

• How can organizations measure the impact of data-driven initiatives on their business performance, and what metrics should be used? 

Saru Malhotra, Team Lead Data and Analytics Strategy – mobile.de 

Pier Martin, Vice President, Data and Analytics - ZEAL Network SE 

Maximilian Ehrlich, Director Data & Insights – TONIES 

During this 5-minute networking session, the aim of the game is to go and meet two people you don't already know.  Have fun! 

This session will explore how organisations can design and structure data teams to maximise efficiency, innovation, and strategic alignment. Key discussions will include: 

• Balancing regulatory compliance, data security, and business agility through robust governance frameworks. 

• Integrating AI and machine learning capabilities within data teams to drive innovation and maintain competitive advantage. 

• Leveraging advanced data architectures and technologies (e.g., data lakes, data warehouses, and cloud platforms) to scale operations and enable data-driven decision-making. 
• Fostering a culture of data literacy and continuous improvement, ensuring employees at all levels are empowered to leverage data effectively.

Aleksejs Plotnikovs, Founder of chiefdata.ai, and former Lead of Data & AI Strategy at Microsoft 

Olga Ivina, Global Head of Data Science Engineering – MICROSOFT 

Jesse Rothenberg, Head of Data & Insights Unit – ABLETON 

Financial data teams operate in an environment where agility and innovation must align with strict governance and compliance requirements. Establishing the right infrastructure is essential to maximize efficiency while ensuring security and regulatory adherence. 

This talk explores how organizations can design governance frameworks that protect data assets without hindering business agility, leverage modern data architectures (data lakes, warehouses, and cloud solutions) to scale effectively, and facilitate seamless transitions from research to production. Insights will be drawn from building a quantitative investment infrastructure from the ground up, addressing key challenges such as high availability, versioning, real-time data access, and compliance. 

By examining strategies that balance security with flexibility, this session provides practical takeaways for designing IT-safe, governance-aligned setups. Additionally, the discussion will highlight how collaborative platforms, and structured workflows can enhance efficiency across infrastructure and development processes. 

Rudi Bauer, CEO –INFRAFIN 

Hendrik Steinbach, Senior Associate & Lead Data Scientist -neXDos 

An informal, interactive session where attendees ask questions directly to an AI ethics and data privacy expert. The expert will answer questions on the fly, providing practical insights and advice on navigating regulations and building trustworthy AI systems. 

Focus Areas: AI ethics, data privacy, regulatory challenges. 

Olga Ivina, Global Head of Data Science Engineering – MICROSOFT 

AI investments must serve business goals, not the other way around, to drive growth and competitiveness. Organizations need to directly link their data strategy with business objectives to achieve sustained profitability. The presentation demonstrates how combining strategic alignment with organizational maturity enables AI profitability scaling across companies of any size, whether public or private.  

Self-service analytics can be a game-changer for product teams, helping them move faster and make better decisions without relying on data specialists. Divya Bokaria has done exactly that at ZATTOO, setting up analytics events, tools, and training to put data directly in the hands of product teams. In this session, she’ll share her experiences and key takeaways. 

🔹 Turning Data into Action – How she heled built the right setup to help teams make informed, data-driven decisions. 
🔹 Breaking Down Barriers – Making data accessible and usable without creating bottlenecks. 
🔹 From Insight to Impact – Real examples of how self-service analytics helped product teams iterate faster and drive growth. 

• How do organisations determine which datasets require governance when faced with an overwhelming volume of information? 

• What are the key hurdles in maintaining regulatory compliance during governance initiatives, and how can these be effectively managed? 

• In what ways can adaptable governance models promote tailored and secure access to data across diverse business needs? 

• What practical steps can dismantle data silos between departments to drive faster, more informed decision-making? 

• How can aligning data governance efforts with organisational culture and stakeholder priorities strengthen governance frameworks? 

Dr.-Ing. Susan Wegner, Head of Global Data and AI – ALLIANZ 

Alexander Yasnogor, VP of Data - FINN 

• How to use data analytics to optimize operations and drive cost efficiencies  

• Aligning business strategies with sustainability objectives using data insights  

•  Ethical data use, transparency, and governance in decision-making  

• Overcoming common challenges in implementing data-driven strategies in complex industries 

Dr. Christian Essling, Global Head of Data and AI – E. ON Technology 

Francesco Di Costanzo, CEO – JAJA FINANCE 

Valeriy Arsentyev, Head of Data - HUMANOO 

Francesco Di Costanzo, CEO – JAJA FINANCE 

• What strategies can organizations adopt to identify and monetize untapped data assets while maintaining compliance with GDPR and other regulations in the German market? 

• How can businesses create scalable data products or services that deliver value to external customers and internal stakeholders without compromising operational efficiency? 

• What role do emerging technologies like AI, IoT, and predictive analytics play in transforming raw data into profitable revenue streams across industries such as manufacturing and finance? 

• How can organizations balance data monetization efforts with ethical considerations and customer trust to ensure long-term commercial success? 

Aleksejs Plotnikovs, Founder of chiefdata.ai, and former Lead of Data & AI Strategy at Microsoft 

Sebastian Schwarz, Head of Data & AI – Customer Solutions - E. ON Technology 

Tim Renner, Head of Business Analytics - KROMI Logistik GmbH  

• What are the core principles of effective data management? 

• How can robust data management practices speed up digital transformation initiatives? 

• In what ways can data management enhance decision-making and drive business innovation? 

• What strategies can overcome common challenges in data management?

Sandeep Murali, Global Director of Data Excellence and Business Analytics -MUNDIPHARMA