CONFERENCE PROGRAM OF 2021
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.
Governing big data and analytics
Data volumes are exploding, and companies are striving to use advanced analytics for more data-driven insights and self-learning systems. Enabling scalable data onboarding and analytics delivery processes with little human intervention but strong governance is key to extract value from Big Data and Analytics successfully. The CC CDQ has developed a framework for governing Big Data and Analytics in close collaboration with industry partners. The framework supports practitioners to setup processes, roles and tools to scale analytics use cases.
Target Audience: Analytics Manager, Data Manager, Project Leader
Prerequisites: Basic knowledge and some experience in analytics or data management
Level: Basic
Martin Fadler is researcher in the Competence Center Corporate Data Quality (CC CDQ) and doctoral candidate at University of Lausanne. Before joining CC CDQ, he worked for several years as a Data Scientist in a venture of Deutsche Telekom. His research interests relate to data management in the context of big data and analytics, and on how artificial intelligence, in particular machine learning, can improve data management.
Christine Legner ist Professorin an der Universität Lausanne und leitet das Competence Center Corporate Data Quality (CC CDQ), in dem sie und ihr Team gemeinsam mit 20 europäischen Unternehmen innovative Konzepte und Lösungen für das Datenmanagement erarbeiten. Sie verfügt über langjährige praktische und akademische Erfahrung und ist Autorin aktueller Studien zu Datenstrategien und Datenkatalogen.
Martin Fadler,
Christine Legner
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