The deadline for Proposals has expired.
The fourth data2day conference is to be held in Heidelberg, Germany, on September 26 to 28, 2017. The event will focus on the whole range of topics associated with Big Data, Data Science, and Machine Learning. It aims to present fundamental knowledge as well as experiences from practical work and informs bout the most important theories, tools, and technologies.
Three partners in the field of computing/IT have teamed up to host the conference: heise Developer, the online channel for software development; dpunkt.verlag, publisher of reference books for the professional computing scene; and iX, the magazine for professional information technology. The hosts invite you to submit your proposals on one or more of the following topics until May 2nd, 2017:
Concepts and Implementations
- Smart Data: intelligent creation of value for Big Data
- Fast Data: design and setup technologies needed to extract data in a fast and efficient way
- Secure Data: methods and strategies to protect business data, strategies for cases of emergency
- Blueprints for Big Data architectures
- Data Hubs/Data Lakes
- Distinctions between classica Data Warehousing and new approaches
- Internet of Things (IoT)
- Data protection and other legal aspects
- Adjusted and new job descriptions
- Apache Hadoop and its ecosystem, distributions and other platforms, frameworks, and tools for analysis of structured and unstructured measured data
- Technologies for full-text and real-time search
- Established programming languages for analyzing, processing and transfering data, query languages
- NoSQL and NewSQL Stores
- In-Memory databases
- In-Memory-Computation Grids
- Event-Processing systems
- Content Delivery Networks
- Data services in the Cloud
- Free versus commercial tools
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.
Machine Learning and Artificial Intelligence
- Data Science
- Machine Learning and Deep Learning (Convolutional Neural Networks, Bayes'sche Netze, CRFs, SVMs, Genetische/Evolutionäre Algorithmen, Decision Trees ...)
- Cognitive Computing
- Computer Vision, natural language processing, image and voice recognition
- Predictive analytics
- Knowledge acquisition, representation, networks
- Connecting to Big Data systems such as Apache Spark
- ML libraries and frameworks such as TensorFlow and Caffee
- Ethical aspects
- Ongoing and completed projects that have implemented Big Data, Data Science, Machine Learning and similar approaches
- Migrating classic data warehouse and business intelligence projects to Big Data & Co.
- Use cases that have led to measurable improvements in business through data analysis
- Use of Tools for modern data-centered applications (presented in the context of specific areas of application and usage scenarios)
- Interaction and integration of different tools
Please indicate your preference for a presentation lasting up to 70 minutes or for a short session of up to 40 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 , . The complete schedule will be available online end of May.
Conference board members are: Mikio Braun (Zalando), Klaas Bollhöfer (The unbelievable Machine Company), Bernd Fondermann (brainlounge), Lars George (OpenCore), Uwe Haneke (Hochschule Karlsruhe), Alexander Neumann (heise Developer, responsible), and René Schönfeldt (dpunkt.verlag, responsible).
Please contact us with questions regarding the conference or the schedule of events: email@example.com