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On this site, there is only displayed the English speaking sessions of the TDWI München digital. You can find all conference sessions, including the German speaking ones, here.
The times given in the conference program of TDWI München digital correspond to Central European Time (CET).
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Thema: Cloud
- Montag
20.06. - Dienstag
21.06. - Mittwoch
22.06.
Machine learning and AI have changed the world of data processing and automation at a breathtaking pace, at the cost of turning algorithms into hard-to-control and monitor black boxes.
We present methods and concepts of explainable AI that aim to open the black box and tame these algorithms.
Target Audience: Decision-Makers/Stake Holders in AI & model development, Data Scientists
Prerequisites: general awareness of modeling pipeline and challenges, no coding/math skill required
Level: Basic
Maximilian Nowottnick is a Data Scientist at the full-service data science provider Supper & Supper GmbH from Germany. He has a B.Sc. and a M.Sc. in Physics and extensive knowledge in developing AI solutions in the areas of GeoAI and Mechanical Engineering. He was one of the driving engineers to develop the first SaaS solution of Supper & Supper, called Pointly for 3D point cloud classification.
Natural Language Processing (NLP) allows us to deeply understand and derive insights from language, ultimately leading to more automated processes, lower costs, and data-driven business decisions.
Google is recognized as a market leader in AI and has built a range of solutions incorporating NLP to address a myriad of business challenges. This talk will introduce a few possible solutions, as well as some business use cases on how to incorporate them in a variety of industries.
Target Audience: Middle and upper-level management, Business users with AI/machine learning challenges, BI/Data professionals
Prerequisites: Basic knowledge of machine learning and cloud technology, interest in NLP
Level: Intermediate
Catherine King is a Customer Engineer at Google Cloud and is a Google Cloud Certified Professional Data Engineer. She works with customers in the Public Sector and supports them in digital transformations, big data analytics, and artificial intelligence implementations. Before Google, she worked for many years in the Translation Industry designing Machine Translation models for enterprise clients.
Catherine holds an MSc in Data Science and is passionate about decision science and data-driven cultures.
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SWICA historically runs a data warehouse built by a centralized team and in parallel, multiple isolated solutions for domain specific analyses, which afford high maintenance and an extensive effort to stay compliant.
Modernizing our analytical environment, we are building a collaborative platform on MS Azure, utilizing the Data Mesh paradigms of data domain and data product.
We aim to deliver a managed data marketplace for all data domains to provide their data products on a modern platform with low maintenance and built-in security & compliance.
Target Audience: Data Analysts, Data Engineers, Project Leaders, Decision Makers
Prerequisites: Basic understanding of the data mesh concept, data warehouse architectures and the challenges of diverse analytical use cases from multiple lines of business
Level: Advanced
15 years of BI industry experience as a project manager, analyst, team lead and solution architect. Closely following new concepts and technologies, aiming for practical application in the enterprise world.
Building planning and reporting solutions for small and medium-sized enterprises for more than 15 years, the opportunity to build a modern cloud based data platform for SWICA the leading health insurance company in Switzerland, is a challenge to develop my personality and skills. A special candy comes with the usage of the latest cloud technologies and a high flexibility for building the solution.
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Petrol is Slovenian company that operates in 8 countries in SEE with 5BEUR annual revenue. As traditional publicly-owned company, Petrol has faced necessity for transformation to stay ahead in highly competitive market. Use of BIA was mainly reactive, but in recent years it has transformed into competitive advantage by using cloud technologies and industry specific analytical models and focusing on the content and creating business value. This value is now being leveraged as competitive advantage through proactive use of data and analytics.
Target Audience: Decision Makers, Data Architects, Project Managers
Prerequisites: None
Level: Basic
Extended Abstract:
Petrol is Slovenian company that operates in 8 countries in SEE with 5BEUR annual revenue. Main business activity is trading in oil derivatives, gas and other energy products in which Petrol generates more than 80 percent of all sales revenue and it also has a leading market share in the Slovenian market. Petrol also trades with consumer goods and services, with which it generates just under 20 percent of the revenue. Use of BIA was mainly reactive, but in recent years it has transformed into competitive advantage by using cloud technologies and industry specific analytical models and focusing on the content and creating business value. This value is now being leveraged as competitive advantage through proactive use of data and analytics. Presentation will cover main business challenges, explain technology architecture and approach and discuss results after three years of system development and use.
Andreja Stirn is Business Intelligence Director with more than 20 years of experience working in the Oil & Energy and Telco industry. Skilled in Data Warehousing, Business Intelligence, Corporate Performance Management, Market Research and People Management.
Dražen Orešcanin is Solution Architect in variety of DWH, BI and Big Data Analytics applications, with more than 25 years of experience in projects in largest companies in Europe, US and Middle East. Main architect of PI industry standard DWH models. Advised Companies include operators from DTAG, A1 Group, Telenor Group, Ooredoo Group, Liberty Global, United Group, Elisa Finland, STC and many companies in other industries such as FMCG and utilities.
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Zum Management einer Bonus Club Karten Lösung mit mehreren Geschäftspartnern musste binnen kürzester Zeit eine BIA Lösung aufgebaut werden.
Im Vortrag wird gezeigt wie die Anbindung der Geschäftspartner über Cloud und OnPrem Komponenten erfolgt und mittlerweile seit Beginn dieses Projektes 16 individuelle Partner DWH Lösungen inkl. einer Unified DWH Lösung aufgebaut wurden.
Die DWH Lösungen selbst wurden On Prem implementiert. Die Reporting Anbindung der Geschäftspartner inkl. der Data Mart Schicht liegt dann wieder in einer Cloud Umgebung. Im Vortrag wird auf die Herausforderungen und Lösungsansätze im Zuge der Umsetzung dieser komplexen hybriden Architektur eingegangen.
Gregor Zeiler ist seit dreißig Jahren in verschiedenen Funktionen in der Business Intelligence-Beratung tätig. Im Zuge seiner beruflichen Tätigkeit konnte er umfangreiche Projekterfahrung in vielen Branchen und auf Basis eines breiten Technologiespektrums sammeln. Zahlreiche Publikationen und Vorträge begleiten seine berufliche Tätigkeit. Als CEO bei biGENIUS AG kommt er seiner Passion die Prozesse in der Entwicklung von Data Analytics Lösungen zu optimieren nach.
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