Call for Proposals

The thirteenth data2day conference is to be held October 7th and 8th 2026. The event is dedicated to Data Scientists, Data Engineers und Data Teams. It will focus on fundamental knowledge as well as experiences from practical work and present the most important theories, tools, and technologies Data Teams need to proceed on their way towards the data-driven company.

Two partners in the field of computing/IT have teamed up to host the conference: iX, the magazine for professional information technology (and software development) and dpunkt.verlag, publisher of reference books for the professional computing scene. The hosts invite you to submit your proposals on one or more of the following topics by April 15, 2026:

Submit Proposals

Data Platforms & Engineering

Modern Data Architecture: Data Warehouse, Data Lake, Data Lakehouse, Data Mesh, Data Fabric...
Data Management & Quality: Data Ingestion, ensuring accurate and reliable data, Metadata Management...
Data Contracts: Guarantee Data Quality for Data Producer and Consumer
Data Processing: ETL vs. ELT, Streaming Data and Big Data Systems like Apache Spark...
Databases: SQL, NoSQL, NewSQL, In-Memory, GraphDBs...
Generation of Synthetic Data: Methods and use cases for artificial, privacy-compliant training data

MLOps, DataOps & Automation

MLOps for the entire lifecycle: From experiment to robust, productive model
Special case LLMOps: Challenges in training, deployment, and cost management of LLMs
ML Platform Engineering: Building internal self-service platforms for data science teams
Automating Data Pipelines: DataOps, GitOps and CI/CD for data processes
Testing & Monitoring: Testing tools and frameworks along the entire data and ML pipeline

Generative AI & Advanced Machine Learning

Generative AI in practice: Agentic AI, autonomous systems, and multimodal applications (text, image, audio, video)
Developing LLM Applications: Retrieval-Augmented Generation (RAG), Fine-Tuning and advanced Prompt Engineering
Infrastructure for Generative AI: Vector databases – selection, implementation, and scaling
Classical and Deep Learning: Computer Vision, Natural Language Processing, Image and Speech Recognition, Predictive Analytics
ML-Frameworks and Libraries: Practical insights into TensorFlow, Keras, PyTorch, etc.
Efficiency and On-Device AI: Model compression, inference optimization, and privacy-friendly GenAI applications on end devices (Edge AI)

Data Skills & Value Creation

Core Data Skills: Programming languages (Python, R, etc.), data modeling, and statistical fundamentals
Data Visualisation & Storytelling: Present results in a clear and understandable way and communicate them convincingly
Self-Service-Analytics: Enable domains and departments to work independently with data
Data-driven Product Development: From the initial idea to the data-driven product or service
Industry-specific solutions: Specific use cases and best practices from the fields of law, fintech, medicine, industry, marketing, etc.
Use Cases & Testimonials: Lessons Learned, Success Stories and Failures from ongoing and completed projects

Data Strategy, Governance & Culture

AI Regulation & Compliance: Practical implementation of the EU AI Act, EU Data Act, classification of AI systems, and technical consequences
AI Governance & Ethics: AI auditing, bias benchmarking, explainable AI (XAI), and the copyright debate surrounding training data
Sustainability & Green AI: Development of resource-efficient AI and the use of AI for environmental sustainability goals
Becoming a Data-driven Company: Strategies, organizational hurdles, and breaking down data silos
Data Literacy & Team Topologies: Building data literacy throughout the company and successful collaboration between domain experts and data specialists
Data Teams: Onboarding, management, and agile process models (e.g., Data Canvas, CRISP-DM, DASC-PM)
Data Security & Sovereignty: Compliance, Data Privacy, Governance & Data Spaces

The emphasis will be on hands-on introductions, conceptual decisions, live demos, or comparison of different techniques. Presentations that are based solely on promoting a product will not be allowed.

Talks should be up to 45 minutes. Tutorials have been scheduled for full days (6-7 hours). Please send a target-group-specific abstract (400–700 characters) of your proposed presentation. Supplementary materials (long abstracts, slides, Proposals, etc.) are also welcome.

The deadline for submissions is April 15, 2026. The complete schedule will be available online by mid of May.

Submit Proposals

Find the members of the conference board here.

Please feel free to contact us with questions regarding the conference or schedule of events events@dpunkt.de

Please use the online form.