September 18-20, 2022 | Germany
The 10th Big Data Minds offers decision-makers from the DACH region a tailor-made platform to discuss strategy concepts in the context of Big Data & Data Analytics and to present successful projects. The leading big data event brings together more than 200 decision-makers and experts for data strategy & analytics to exchange strategies for the internal and external handling of large amounts of data and methods for their analysis and to find effective solutions to your challenges.
November 19, 2022 | USA
The Twin Cities ACM Chapter invites students, faculty, and professionals to CADSCOM 2022! The 4th Colloquium on Analytics, Data Science, and Computing (CADSCOM) will be held in-person and virtually on Saturday, November 19, 2022. CADSCOM provides an excellent opportunity for faculty, students, and professionals to share their original research in data science, analytics, and computing. The submissions are peer-reviewed and double-blind reviewed. The colloquium will feature prominent keynotes, industry-faculty panels, and peer-reviewed papers. CADSCOM 2022 has been approved by the Association for Computing Machinery (ACM) as a chapter conference.
November 15-16, 2022 | Canada
New to Western Canada this year, CDAO Calgary is designed for Chief Data Officer (CDO), Chief Analytics Officer (CAO), and senior data & analytics roles in Calgary and the surrounding provinces of Canada.
This forum is led by CDOs, CAOs, and CDAOs but is open to all IT, Data, and Analytics Leaders from industries like Financial Services, Oil & Gas, Manufacturing, Retail, Tourism, and more, to allow you to meet and network with the very best of your peers from a range of organizations and experiences. Our attendees are Senior Data & Analytics Leaders who need to attract next-generation workers, build data-fueled teams and organizations, and insist on data transparency so they can modernize their teams, and improve data ROI.
November 21-24, 2022 | China
There are many software and systems dealing with big data, but data mining models and machine learning methods are usually difficult to be directly applied to those software and systems. To make the research model or method support the operation of the big data systems, it is necessary to adaptively reconstruct the method, or propose data processing methods suitable for specific needs. We welcome research papers on *every* topic related to the principles and theory of data mining in the big data system, provided that there is a clear connection to foundational aspects. This includes papers exploring existing or identifying new connections between data mining in the big data system and other areas, such as the areas of: