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Sarah Rojewski
Digital Service Manager / Projektleitung von Aura, der künstliche Intelligenz von Telefonica

• Presentation: Usage of AI to create a new customer relationship built on trust

• Aura is Telefonica’s global artificial intelligence with the aim to create a new customer relationship based on trust. Aura offers a personalized experience, with real-time answers using natural language processing. The cognitive intelligence is available independently of the channel and the vision is to create an omnichannel experience so that Aura becomes an identification factor for the customer. But not only NLP itself is the key essential for a successful and trustful conversation between humans and technology. Providing the customer with personalized information which goes beyond a simple question answers dialogue is the goal of Telefonica’s 4th platform. The 4th platform is the brain of Aura and many more use cases using machine learning, normalizing data and data models.

• Biography: Sarah Rojewski is Digital Service Manager at Telefonica GmbH & Co. OHG and project manager for the implementation of the global artificial intelligence of Telefonica "Aura". Sarah is the interface between the business requirements of Digital Transformation, technology providers such as Microsoft and Amazon Web Services and supports the company's vision to roll out artificial intelligence across all relevant customer contact channels and provide the customer with a consistent omnichannel experience. The original humanities scholar aims to take service digitization to the next level and not only to create a better experience for customers but also internally develop employees and create new career opportunities.

Julia Kraus
Data Scientist. Experience in deep learning, ML and statistical methods for engineering and time-series forecasting.
B / S / H (Bosch Siemens Haushaltsgeräte)

• Presentation: Find Your Balance – A Guide to Effectively Dealing with Imbalanced Datasets

• Imbalanced classes appear in machine learning classification where there are more instances of one class than the other. This often is the case, for example, in medical diagnostics and predictive maintenance. Machine Learning algorithms tend to produce unsatisfactory classifiers when faced with imbalanced datasets. This talk aims at providing guidelines to effectively dealing with this issue. We will have a look at data with imbalanced classes and see how the imbalance can affect the predictions. We will then dive into different techniques for dealing with imbalanced data and compare how different models perform on several data sets.

• Biography: Julia Kraus completed her M.Sc. in Mathematics at LMU Munich. She got enthusiastic about machine learning during her master’s thesis for which she worked on a machine learning use case for autonomous driving. She now has been working as a data scientist for three years, focussing on Machine Learning for industry 4.0 use cases.

Ilka Landsmann-Kropp
Product Owner BI/Data Warehouse
limango GmbH - A member of the otto group

• Presentation: BI is not a given – An experience report of bringing data in a medium-sized company

• Medium-sized companies know of their massive data and if used correctly how much impact these data can have on their success. However, for them, it is often not obvious to implement a Business Intelligence. Challenges that might come up are: Is a BI really necessary? How to combine new knowledge and old reportings? How to build a successful data team? How to establish a data-driven mindset within the business units? In this talk, I share my experiences of building a data team and make the BI visible encourage departments to use data more efficient and face their pain points to solve them with data.

• Biography: Ilka Landsmann-Kropp joined limango as an IT developer for Customer Relationship Management after having her third child. In her second year with the company, she decided to support the BI team as a developer. At that point, the BI team was already struggling and as a result of that, she was confronted with the task of rebuilding the team and making it visible again within the company. Today she is responsible for the BI team as its Product Owner.

Isabel Grund
Cloud Solution Architect Azure

• Presentation: Achieving integration through education - How Microsoft is teaching refugees about AI

• One of the biggest challenges that companies are facing today is finding the right people to work on data related projects. On the other side there are many refugees coming to Germany who are interested or have already worked in this field but are not quite ready yet to enter the German job market. Microsoft is working on bridging this gap, together with ReDI School and companies like Moxa and BMW. This is being done through different initiatives, for example the Big Data program. Find out more about the data project we are working on within this program and maybe even become a teacher yourself!

• Biography: Isabel Grund is a Cloud Solution Architect at Microsoft working in the field of Azure Data and AI. She has been at Microsoft for over 4 years after doing her Master’s in Business Informatics. Her main focus is on working with Manufacturing customers on large scale IoT projects, where huge amounts of data are being streamed and analyzed on the Azure platform.