
Please note:
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).
By clicking on "EVENT MERKEN" within the lecture descriptions you can arrange your own schedule. You can view your schedule at any time using the icon in the upper right corner.
Thema: Financing
- Dienstag
21.06. - Mittwoch
22.06.
In der schieren Menge an Daten, die in vielen Unternehmen schlummern, steckt ein enormes Wertpotential für das Business. Doch wie versetzen sich Organisationen in die Lage, diesen Datenschatz zu heben? Datensilos und heterogene Datenbestände scheinen oftmals eine unüberwindbare Hürde für eine nahtlose Integration zu sein – und die IT wird schnell zum Spielball aufwändiger und teurer Legacy Integrations-Technologien. Im Vortrag erfahren Sie von Robert Auerochs, wie die ING-DiBa diese Hürden in der Datenintegration und -nutzung überwindet und hierauf innovative und gewinnbringende Use-Cases aufsetzt.
Zielpublikum: Data Engineers, Data Scientist, Data Architects, Data and Analytics Manager, Chief Data Officer(CDOs), Chief Information Officer (CIOs), Data Analysts, Heads of Data Integration etc.
Voraussetzungen: Basic knowledge of data and analytics, especially data warehousing and data transformation processes and understanding of these in the larger organizational context to achieve the business goals
Schwierigkeitsgrad: Fortgeschritten
Robert Auerochs ist in seiner Funktion als Expertise Lead DataLake Platform seit über 13 Jahren bei der ING-DiBa beschäftigt. Er ist zudem als Freelancer im Bereich Spiel-Design und Referent an der TU Darmstadt tätig.
Der Einsatz von Künstlicher Intelligenz zur Betrugserkennung bei Heilmittel- und Pflegeleistungen in der gesetzlichen Krankenversicherung. Von der Pseudonymisierung und Digitalisierung der Abrechnungsbögen bis zur Analyse, Auswertung und Darstellung der Anomalien - Ein Projektbericht!
Zielpublikum: Management, Data Scientists, Data Engineers
Voraussetzungen: Experience, Curiosity
Schwierigkeitsgrad: Fortgeschritten
Team Lead and Business Development in several companies.
Team Lead, Data Mining and Neural Network Specialist
The Coronavirus lockdowns altered public transport occupation data. Ultimately, these changes in occupation data are perfect examples of sudden concept drifts that can be blockers in most machine learning deployments. We managed to overcome the obstacles by developing methods and engineering features that allowed us to adjust forecasts based on unforeseen changes in the occupation data. In this talk, we give insights into our journey from idea development to the ways how we overcame the challenges and share our learnings.
Target Audience: Data Engineers, Software Architects, AI Architects, Data Scientists
Prerequisites: Experience in Time Series. Basic understanding of machine learning
Level: Expert
Extended Abstract:
Machine learning projects often view and predict a snapshot interval of reality. We machine learning engineers often forget that the real world is not static at all.
After all, we got hit by the Coronavirus reality rendering countless machine learning models useless.
The changes in public transport occupation out of Corona lockdowns is a perfect example of these so-called concept drifts.
The instability of the machine learning models when concept drifts are appearing result in immense problems for the reliability and predictability of the AI.
Therefore, we dig into this problem and show how we solved this challenge for the case of concept dirfts in public transport occupations.
Dr. Tim Frey is co-founder of the company iunera GmbH and Co. KG. Among other things, he holds a PhD from the University of Magdeburg and loves to design data-driven scenarios and applications. His computer science background is in the area of Business Intelligence and platform architecture.
Vortrag Teilen
Vortrag Teilen