Moderne Datenorganisationen:
Auf der Reise zwischen Federated Data Lake, Data Fabric, Data Mesh bis zu Data Products, Data Marketplace, Data Governance
HOHE SKALIERUNG - LIEFERFÄHIGKEIT - FLEXIBILITÄT
08 - 09 April, 2025
| Metropolitan Hotel by Flemings, Frankfurt am Main
Agenda Day 2 | MITTWOCH, 09.04.2025
7:30 am - 8:00 am
Welcome coffee and Registrierung für die Masterclass
Masterclasses
8:00 am - 9:30 am
MASTERCLASS B: MINDSET CHANGE AND CULTURAL CHANGE IN A COMPLEX DATA ORGANIZATION
Tobias Riedner -
Head of Data Analytics,
Danone
In times of data transformation and the change to data-driven corporate models, such as the Data Mesh, one of the greatest challenges is cultivating a new mindset among employees. The transformation towards decentralization brings with it new questions. In this workshop we will address this topic and discuss the following aspects:
- Dealing with the new data-related roles and responsibilities in the specialist departments in a decentralized organization (data literacy and mindset)
- Processes to increase know-how (“what does that mean” or “what does that NOT mean”)
- Designing change management and cultural change correctly
- Practical insights through case studies and tools to actively implement the change in your complex data organization
8:00 am - 9:30 am
MASTERCLASS C: NAVIGATING THE DATA MESH JOURNEY: PRACTICAL INSIGHTS AND LESSONS FROM LUFTHANSA GROUP ANALYTICS PLATFORM
Gramoz Krasniqi -
Information Technology System Architect,
Lufthansa Group
Rishabh Goyal - Solutions Architect, Lufthansa
Rishabh Goyal - Solutions Architect, Lufthansa
In this masterclass, we delve deep into the practical aspects of implementing a Data Mesh architecture from an Analytics Platform perspective, drawing from Lufthansa’s own experiences and lessons learned. This session will provide actionable insights and realworld examples of how a global enterprise like Lufthansa has tackled challenges and reaped benefits from a Data Mesh approach.
Platform Strategy for Advanced Analytics
Building Scalable and Cost-Efficient Analytics Platforms
Self-Service Analytics Capabilities
Integration and Harmonization of Data for Analytics
Governance in Decentralized Environments
Session 3
9:30 am - 9:40 am
Welcome and Opening
9:40 am - 10:00 am
Lessons Learned from Data Architectures for Practical Data Mesh and Governance
Haydar Vural -
Chief Digital Officer (CDO),
Karsan Automotive
- Building flexible and low-cost data architectures to allow effective mesh implementations
- Governance in distributed environments
- The role of business units as data owner in decision-making and supervision
- Open source tools and and their pros/cons
10:00 am - 10:30 am
Implementing a Data Product Platform: Experiences and Techniques
Dr. Matthias Nicola -
Field CTO,
Snowflake
- Common challenges in data mesh and data product implementations
- Bundling data & metadata into a cohesive data product
- Internal Marketplace: Document, share, discover, and request data products
- Implementing cross-domain governance and access control
- Data product quality management
10:30 am - 11:00 am
Panel Discussion: Technical aspects of Decentralized Data Architectures
Marc Barisch -
Chief Architect Data Integration,
Siemens
Romain Thibault - Program Manager, Data Strategy, mobile.de
Shane Houdek - Head of Data Architecture, IKEA | Ingka Group
Søren Meincke Persson - Head of Data Engineering, Norlys
Philipp Nacke - Tech Lead Databricks, flaschenpost
Fernando Veiga Fonseca - Head of Engineering, C&A
- What technologies fit best? DWH vs. Data Lake vs. Data Lake House
- Setting the base frame and connecting to strategy
- Connecting the engineering teams
- Success strategies towards next steps of implementation
- Domain-Oriented Data Ownership, Scalability and Performance, Federated Computational Governance
11:00 am - 11:30 am
Kaffeepause mit Networking-Gelegenheit
11:30 am - 11:50 am
Empowered Product Teams in Action: Scaling Innovation with Data Mesh at Vista
Dr. Jannik Podlesny -
Principal, Data & Analytics,
Cimpress / Vistaprint
- Orchestrating high-performing product teams as a data mesh to manage 9.5 billion messages/day, 200,000 analytics sessions/day, and 7,000 API clients, with over 800 engineers driving innovation
- Scaling federated computational governance using automated crawlers and how Vista enables freedom in the accountability framework with FinOps
- How a remote-first culture fosters a rapid development environment and pushes the boundaries of what is possible with high-performing teams
11:50 am - 12:10 pm
IKEA’s journey towards a FAIR data ecosystem – From business need to data mesh adoption
Nick Martijn -
Director Data Management & Data Platform,
IKEA | Ingka Group
- Why our business needs a FAIR data ecosystem (data products)
- What we aim to build - Our data mesh architecture and setup
- How we aim to inner-source and drive adoption of components – develop services together and for the many
- Learnings so far – Key learnings from our journey so far
Round Table Sessions
Table A
12:10 pm - 12:40 pm Table A: Data Ownership Accountability & Governance in a Decentralized Architecture Pascal Moritz - Head of AI Architecture and Data Engineering, Miele- Establishing clear ownership roles for data assets within a decentralized architecture to enhance accountability and responsibility
- Implementing robust governance frameworks to regulate data usage, access, and quality across decentralized data domains
- Ensuring compliance with regulatory requirements and industry standards while promoting transparency and trust in data handling practices within the data mesh paradigm
Table B
12:10 pm - 12:40 pm Table B: Agile methods in data governance and data quality management Dr. René Börner - PO Data Analytics, Deutsche WertpapierService Bank- Definition of the agile way of working in data governance
- Measurable improvements in efficiency compared to “classic” methods
- Balance between agility and governance, scalability and security
Table C
12:10 pm - 12:40 pm Table E: DWH vs. Data Mesh Santosh Sutrave - Senior Global Enterprise Architect, E.ON Digital Technology• Which approach is right for your business? Pros and cons for each approach
• Choosing the right governance
• Agility and scalability
12:40 pm - 2:00 pm
Lunch Break and Networking
Afternoon Session
DATA MANAGEMENT AND ARCHITECTURE TRACK
2:00 pm - 2:20 pm The use of AI in Master Data Management Dr. Yaniv Noar - Director - Head of Global Master Data Management, Sandoz- Automated Data Quality: AI enhances data accuracy by automating cleansing, deduplication, and enrichment processes
- Predictive Data Management: AI anticipates data issues and optimizes future data needs through predictive analytics
- Efficient Data Governance: AI ensures compliance by automating governance rules and monitoring data integrity
- Applying generative AI in MDM
DATA MANAGEMENT AND ARCHITECTURE TRACK
2:20 pm - 2:40 pm Data Lifecycle & Ownership at Volvo Cars Anna Maria Wingö - Data Lifecycle Focus Area Lead, Volvo Cars- What is Data Lifecycle & Ownership Management?
- Why is it important?
- How will it help your organization?
- Insights from Volvo Cars’ Data Lifecycle journey
DATA MANAGEMENT AND ARCHITECTURE TRACK
2:40 pm - 3:00 pm How to model data architecture in big organizations? Dr. Selmin Daniş Öncül - Domain Lead of Corporate Global Enterprise Architecture Team, E.ON Digital Technology- Operational and analytical data
- How is the data architecture at E.ON ?
- Challenges and opportunities with legacy systems
- How to implement AI scenarios to data
Dr. Selmin Daniş Öncül
Domain Lead of Corporate Global Enterprise Architecture TeamE.ON Digital Technology
DATA MANAGEMENT AND ARCHITECTURE TRACK
3:00 pm - 3:20 pm How to keep track - data management and enterprise architecture in harmony Carsten Forstner - Enterprise Architect, Nordex Group- Why data management benefits from enterprise architecture (and vice versa)
- How enterprise architecture and data mesh enable the scaling of data management solutions
- Best practices: successful examples of the integration of data management and enterprise architecture
- How a flexible architecture enables adaptation to changing business requirements
THE JOURNEY TO DECENTRALISATION TRACK
2:00 pm - 2:20 pm Transforming traditional industries: the importance of a solid data foundation and change management , from mess to mesh Olivier Le Poole - Lead Data Products, Van Oord- Short intro to van Oord and her business
- Already decentralized IT and extensive analytics capabilities, but
- Still somewhat siloed and maturity varies from department to department, requires tailored approach
- Propagating hub&spoke and pub/sub for more active data ownership and data sharing to come to all-enveloping data landscape
- Use case: show what works, build traction
THE JOURNEY TO DECENTRALISATION TRACK
2:20 pm - 2:40 pm Journey to a Data Revolution: Transforming Santalucia Manuel Valero Méndez - Head of Big Data, Santalucia Seguros- From Traditional Data Warehousing to Lakehouse Architecture
- Cultivating a Data Culture for Scalability
- Setting the Stage for Future Decentralization
THE JOURNEY TO DECENTRALISATION TRACK
2:40 pm - 3:00 pm How Data Mesh has significantly influenced NordLB’s data world and how the transition works Sven Wilbert - Stellvertretender Gruppenleiter Data Steering, NordLB- How the important principles of the Data Mesh approach were integrated into the bank’s data governance and data architecture
- Central functions, tasks and teams to meet certain organizational and operational requirements
- Cultural issues and organizational frameworks that must be taken into account in the partial transformation to the Data Mesh philosophy
THE JOURNEY TO DECENTRALISATION TRACK
3:00 pm - 3:20 pm The role of data platform in implementing data mesh and how it influences staffing and managing data teams Ramon Horvath - Engineering Manager, H&M- While the devops approach is significant increase compared to earlier practices and is still very valuable for certain kind of developer teams
- With the tech landscape getting more complex, security increasingly important it could create bottlenecks in hiring for and scaling data operations
- A new approach to staffing and managing data teams
