Programm des Data Festivals

am 17. April 2018

data.stage festival.stage alterna.stage
09:45
Begrüßung / Introduction
Alexander Thamm, Dr. Carsten Bange
09:45 - 10:00
10:00
Ten Key Principles on how to Transform a Global Company into a Data Driven Leader (EN)
Dr. Alexander Borek, Head of Smart Data & Analytics, Volkswagen AG & Alexander Thamm, CEO, Alexander Thamm GmbH
10:00 - 10:30
Keynote
Ten Key Principles on how to Transform a Global Company into a Data Driven Leader (EN)Each Data Transformation Journey is different, but there are some solution patterns that can help in traditional industries. The presentation will explore the following questions on how to drive the change towards a truly data driven enterprise...
10:15
10:30
Break
10:30 - 10:45
Break
10:30 - 10:45
Break
10:30 - 10:45
10:45
Decision Automation: How to get there and what to consider (EN)
Dr. Carsten Bange, Founder and CEO, BARC GmbH
10:45 - 11:15
Data Strategy & Organization
Decision Automation: How to get there and what to consider (EN)The increased use of data science and machine learning leads to more models being used in operational processes. Models are also increasingly adopting decisions here, especially when the speed of decision-making or the data basis is no longer manageable for people. But at the moment, however, this is only occasionally and almost coincidental, because many companies lack a strategy to control this change...
Building a Central Hive Metastore in a Multi-Account AWS Cloud Environment (EN)
Raffael Dzikowski, Big Data Engineer, Scout24 Group
10:45 - 11:15
Cloud
Building a Central Hive Metastore in a Multi-Account AWS Cloud Environment (EN)One of the central challenges when providing a Data Lake architecture in a multi-account Cloud setup on AWS consists in offering a consistent, familiar, and easy-to-use access mechanism to it which ideally hides all the nitty-gritty details of varying data formats and data sources, while at the same time making the data available for analysis in a convenient way. A proven abstraction that meets these requirements is a set of relations (tables) that enable analyses using the well-established Structured Query Language (SQL)...
Identification of patterns in TV consumption Seven One Media GmbH (EN)
Igor Rotin, Senior Data Mining Manager, SevenOne Media GmbH
10:45 - 11:15
Pattern Recognition & Deep Learning
Identification of patterns in TV consumption Seven One Media GmbH (EN)The prognosis of TV consumption of target groups related to program genres is the planning and steering basis for many continuative applications for a TV station. This includes content topics for programming as well as the seasonal placement of specific programs. In addition the changing media usage due to the rapid increase of internet distribution has also influenced TV consumption...
11:00
11:15
From 5 to 90 - Scaling a Big Data Team in 2 years (EN)
Joachim Bürkle, Head of and Product Owner, DB Systel GmbH (ZERO.ONE.DATA)
11:15 - 11:45
Data Strategy & Organization
From 5 to 90 - Scaling a Big Data Team in 2 years (EN)ZERO.ONE.DATA, a Corporate Startup of the DB Systel Innovation & New Venture Business Area, is focusing on Big Data (DataOps, Data Intelligence, Data Projects and Business Services). The presentation will describe how ZERO.ONE.DATA has grown from 5 initial Team Members to more than 90 Members within just 2 years. Difficulties in scaling agile Organizations beyond 10 Members and beyond 40-50 Members, will be addressed as well as the impact on the work of a Product Owner...
Analytics on Azure - Architekturvarianten und Praxisfälle (DE)
Dr. Andreas Stadie, Head of Analytics, EnBW AG und Yello Strom
11:15 - 11:45
Cloud
Analytics on Azure - Architekturvarianten und Praxisfälle (DE)Seit 20 Jahren rücken Data Science und Informatik kontinuierlich enger zusammen. Der aktuelle Meilenstein dieser Konvergenz sind die statistisch analytischen Fähigkeiten der Cloud Systeme. Es gibt bereits ein Reihe von Nutzungsmöglichkeiten der analytischen Cloud Services mit verschiedenen Vor- und Nachteilen. In dem Vortrag werden einige Praxisfälle aus dem täglichen Massenkundengeschäft aufgegriffen und deren Implementierung in der Azure Cloud erläutert.
Deep Learning with medical images (EN)
Dr. Marie Piraud, Senior Researcher, TU München
11:15 - 11:45
Pattern Recognition & Deep Learning
Deep Learning with medical images (EN)In this talk, I will give an introduction of Deep learning in the medical field, and in particular its application to the processing of medical images. Medical computer Vision is a field of Data Science which has its own specificities and challenges, such as data scarceness and variability, and where the black-box aspect is a big drawback. As a use case, we will present the work carried out in the Image-Based Biomedical Modeling research group of the TU Munich...
11:30
11:45
What is the big in (Big) data? And how lean can your data be... (EN)
Dat Tran, Head of Data Science,  idealo.de
11:45 - 12:15
Data Strategy & Organization
What is the big in (Big) data? And how lean can your data be... (EN)Deep Learning, Artificial Intelligence, Tensorflow, Spark, Flink, Big Data, Smart Data, Hadoop, IoT, Agile, Cloud… There has been a lot of hype around those buzzwords and no they are not names of any Pokemons. In this talk, I want to make some sense out of the buzz nowadays. I will share some of my war stories as well as my own experiences in building up a data science team at the largest price comparison service in Germany.
Building an Operational Data Layer for the Real Time demands of Cloud based applications (EN)
Negib Marhoul, Solution Engineer, DataStax Inc.
11:45 - 12:15
Cloud
Building an Operational Data Layer for the Real Time demands of Cloud based applications (EN)Come and learn the challenges faced with building new cloud based applications and the demands they put on backend systems. Learn from DataStax how our customers use an Operational Data Layer to provide real time analytics and scoring on contextual data, keeping it always on, distributed and scalable. While offloading the backend systems.
Understanding furnishing styles from images (EN)
Christian Nietner, Founder & CTO, RoomAR
11:45 - 12:15
Pattern Recognition & Deep Learning
Understanding furnishing styles from images (EN)RoomAR is a new bleeding edge software product that is targeting retailers and manufacturers in the furniture and home furnishing industry. The software visualizes virtual products in the real world using the RoomAR augmented reality mobile app. The user experience is enriched by personalized product recommendations. With the help of deep learning and computer vision algorithms, the personal interior design style and the actual living situation of users are considered...
12:00
12:15
Lunch
12:15 - 13:30
Lunch
12:15 - 13:30
Lunch
12:15 - 13:30
12:30
12:45
13:00
13:15
13:30
Blockchain - Status Quo and Potentials (EN)
Attendees Thomas Schmiedel , Data Scientist, Data Reply & Sebastian Heinz, CEO, Statworx & Marco Plaul, Data Scientist, Alexander Thamm GmbH
13:30 - 14:15
Blockchain - Status Quo and Potentials (Panel)
Blockchain - Status Quo and Potentials (EN)The blockchain technology has developed into one of the most important disruptors of our times, with potential for changing the economy as a whole in the near future. We will therefore discuss the following questions in the panel...
Best Practices: Warum Blockchain und insbesondere die kognitive CortexPlatform die Datenwelt revolutionieren (DE)
Dr. Georg Loepp, Chief Visionary Officer, Cegeka Deutschland GmbH & Jan Buss, CEO, Cortex
13:30 - 15:00
Workshop
Best Practices: Warum Blockchain und insbesondere die kognitive CortexPlatform die Datenwelt revolutionieren (DE)Als einzige Datenbank bietet die CortexDB – als Kern der CortexPlatform – vollautomatisch die höchste Normalform (6. Normalform) als Index über alle Inhalte aller Datensätze. Zu jedem Wert ist somit bekannt wo und wie häufig dieser Inhalt auftritt. Ergänzend dazu sind alle zeitlichen Verläufe einer Information erkenn- und nachvollziehbar. ...

A 60m Data Challenge: Can You Make It? (EN)
Alexandre Combessie, Data Scientist, Dataiku
13:30 - 15:00
Workshop
Daten Party oder Spaßbremse – Alles eine Frage der Architektur (DE)
Jens Schnettler, Senior Manager, Woodmark Consulting AG
13:30 - 15:00
Workshop
Daten Party oder Spaßbremse – Alles eine Frage der Architektur (DE)Ein Realitätscheck aus dem Big Data- und Advanced Analytics Umfeld. Die fortschreitende Digitalisierung führt zu neuen Anforderungen an analytische Informationssysteme unserer Zeit...
13:45
14:00
14:15
data.networking(1) (EN)
Anna Milaknis, Desing Thinkerin
14:15 - 15:00
Networking
data.networking(1) (EN)„Share your passion for data“ and meet 10 exciting data people in 30 minutes. Bring your business cards and prepare a short introduction about yourself. You’ll spend three minutes exchanging cards and information with a fellow attendee. When the chime sounds, you’ll move on to the next attendee.
14:30
14:45
15:00
Coffee Break
15:00 - 15:30
Coffee Break
15:00 - 15:30
Coffee Break
15:00 - 15:30
15:15
15:30
Data Lake Production @Audi - Architecture, Technologies & Organisation (EN)
Christoph Kreibich, Data Scientist, Audi AG
15:30 - 16:00
Data & AI in Automotive I
Data Lake Production @Audi - Architecture, Technologies & Organisation (EN)Data is an elementary part of the digitalization of production at Audi AG. In order to be able to store and analyze data from vehicle and component manufacturing and logistics in an international production network, a central data lake was set up. The Audi Analytics Platform collects data from all business areas and makes it available for cross-functional analyses...
Hans im Datenglück. Von Mystery Shopping, Social Media & Geodaten – smarte Datenanalysen mit Qlik Sense (DE)
Denys Dertwinkel, Leiter Controlling, Hans im Glück Franchise GmbH & Stefanie Greineder, Operatives Controlling, Hans im Glück Franchise GmbH
15:30 - 16:00
Analytics & Visualization
Hans im Datenglück. Von Mystery Shopping, Social Media & Geodaten – smarte Datenanalysen mit Qlik Sense (DE)Der Besuch eines Burgergrills als besonderer Moment des Glücks. Das ist der Maßstab, an dem Hans im Glück seinen Erfolg misst. Daher setzt Hans im Glück Qlik Sense ein, um sämtliche Daten zum Kundenerlebnis im Blick zu behalten und auszuwerten. Während der Präsentation zeigt Denys Dertwinkel, wie Daten zu Mystery Shoppern, Social Media, den Restaurants und Geoinformationen zu KPIs verdichtet werden.
The Death of Data Science - Towards AI fueled Machine Learning Automation (EN)
Sebastian Heinz, CEO, STATWORX
15:30 - 16:00
Machine Learning & Predictive Analytics
The Death of Data Science - Towards AI fueled Machine Learning Automation (EN)Data Science, machine learning and AI are currently disrupting industries worldwide. However, recent advances in AI as well as the ongoing progress on automation of many data science and machine learning related workflows will disrupt and most likely wipe out data science itself in the future. The talk will give you an understandable overview on state of the art algorithms in the field of AI based ML automation and features practical examples of applying automated machine learning.
15:45
16:00
How data connects cultures, markets, business areas and just by that generates massive potentials (EN)
Dr. Stefan Meinzer, Head of regional analytics services for EMEA, BMW AG
16:00 - 16:30
Data & AI in Automotive I
How data connects cultures, markets, business areas and just by that generates massive potentials (EN)The national sales companies of the automotive industry have the closest contact to the dealers and the customers in the automotive industry. They push on sales and customer interaction. However, due to intercultural differences or language barriers the development of business models is still challenging and thereby requires high human efforts. On the other hand, there is one language that is unique around the world – DATA. Based on a concrete use case, we explain how the BMW Group uses the existing international knowledge to define new data driven business models that will drive customers’ centricity to the next level. With latest machine learning methodologies, skilled data scientists and international automotive experts we let data bundle the strengths to shape the future.
Datendemokratisierung @ Telefónica Deutschland (DE)
Laura Velikonja, Data Scientist, Telefónica Deutschland GmbH & Co. OHG
16:00 - 16:30
Analytics & Visualization
Datendemokratisierung @ Telefónica Deutschland (DE)Vor über einem Jahr hat der Vorstand von Telefónica Deutschland eine ungewöhnliche Entscheidung getroffen: alle Mitarbeiter sollen auf den gesammelten Datenbestand des Unternehmens zugreifen können. Das Analytical Insights Center (AIC) ermöglicht so neue Formen des Arbeitens und Entscheidens in der digitalen Welt. Nun geht der Bereich Business Analytics & Artificial Intelligence der Telefónica Deutschland den konsequenten nächsten Schritt in dieser Entwicklung: von der Datendemokratisierung zur Analytics Demokratisierung...
Big Data Predictive Monitoring meets Blockchain (EN)
Francesco Sbaraglia, Big Data Engineer / Manager, Data Reply & Thomas Schmiedel, Data Scientist, Data Reply
16:00 - 16:30
Machine Learning & Predictive Analytics
Big Data Predictive Monitoring meets Blockchain (EN)One of the most hyped topics about Big Data is Predictive Maintenance. In production, for example, sensor data from machines are analyzed so that the next scheduled maintenance can be accurately predicted in order to avoid downtime costs. Can this same principle also be transferred to IT infrastructures? That\\\\\\\'s what Big Data Predictive Monitoring does. It collects metrics, at various levels of IT systems (e.g., processor, memory, network, ...). The detailed metadata are stored using Hadoop clusters and Timeseries Database. Ultimately, this monitoring serves not only as predictive maintenance, but also to optimize performance and to predict crashes. Unlike from Machines,
16:15
16:30
Predictive Control of R&D Projects in Manufacturing by Analyzing the Project Data Base (EN)
Dr. Max Köhler, Data Scientist, Continental AG
16:30 - 17:00
Data & AI in Automotive I
Predictive Control of R&D Projects in Manufacturing by Analyzing the Project Data Base (EN)R&D Projects in manufacturing are risky! Money must be invested even though the outcome is hard to be determined in advance and possible earnings reveal themselves many months or even years after the project has been finished. Project control often looks for KPIs measuring the state of the project at a given point in time. This approach neither looks ahead nor does it allow root cause analysis...
DATA - PREP - GO! Vorbereitung und Analyse so einfach und begeisternd wie Lego (Sie werden Bauklötze staunen…) (DE)
Oliver Linder, Sales Consultant Team Lead, Tableau Software
16:30 - 17:00
Analytics & Visualization
DATA - PREP - GO! Vorbereitung und Analyse so einfach und begeisternd wie Lego (Sie werden Bauklötze staunen…) (DE)Aus wie vielen Steinen besteht das Taj Mahal? Von welcher Farbe gibt es die meisten Lego Steine? Wie viele Lego Sets gibt es? Diese und andere spannende Fragen beantwortet Oliver Linder in seinem Vortrag. Er zeigt ihnen wie man mit Tableau, umfangreiche und komplexe Datensets blitzschnell aufbereiten und analysieren kann.
Advanced Demand Forecasting through Predictive Analytics at BASF (EN)
Benjamin Priese, Data Science Sen. Manager, Advanced Business Analytics, BASF SE & Dr. Thomas Christ, Chief Data Scientist, prognostica GmbH
16:30 - 17:00
Machine Learning & Predictive Analytics
Advanced Demand Forecasting through Predictive Analytics at BASF (EN)Reliable forecasts are a key factor for an efficient and effective management of supply chains. A new forecasting framework for Demand Planning has been developed and implemented successfully at BASF based on advanced predictive analytics methods and sophisticated information technology...
16:45
17:00
Break
17:00 - 17:15
Break
17:00 - 17:15
Break
17:00 - 17:15
17:15
Condition Based Monitoring (DE)
Rene Ahlgrim, Data Scientist, Zeppelin GmbH
17:15 - 17:45
Predictive Manufacturing
Condition Based Monitoring (DE)Erster Use Case (Prototyp) bei Zeppelin. Use Case Zündkerze --> Wie können wir die Ausfallzeiten von Blockheizkraftwerken (BHKW´s) reduzieren? Hierzu wurden die Daten analysiert und die wesentliche Counter bestimmt die Ausfälle frühzeitig detektierbar machen...
Open Source vs. Kommerzielle Software - Vorteile, Nachteile, Integrationsmöglichkeiten (DE)
Dr. Sebastian Derwisch, Data Scientist, BARC GmbH
17:15 - 17:45
Data Project Implementation
Open Source vs. Kommerzielle Software - Vorteile, Nachteile, Integrationsmöglichkeiten (DE)Open Source Sprachen zur Entwicklung von Advanced Analytics Modellen haben ihre Stärken vor allem in der Datenaufbereitung und der Modellierung. Hier ist der Funktionsumfang groß, die Community oft sehr aktiv und die Flexibilität, die eine Programmiersprache bietet, wichtig. Allerdings gibt es Probleme bei der Performanz, die Iterationszyklen in der Prototypisierung verlangsamen können...
Solving real world data problems faster with Search and Semantics (EN)
Daniel Holgate, Senior Sales Engineer, MarkLogic Corporation
17:15 - 17:45
Semantics
Solving real world data problems faster with Search and Semantics (EN)How can data be better modelled to reflect the real world? Sometimes it takes a combined approach...
17:30
17:45
Big Data @Maintenance: Neue Wege bei den Instandhaltunsprozessen von konventionellen Kraftwerken (DE)
Natividad Jordan Escalona, Officer for Research & Development, RWE Power AG
17:45 - 18:15
Predictive Manufacturing
Big Data @Maintenance: Neue Wege bei den Instandhaltunsprozessen von konventionellen Kraftwerken (DE)Im Rahmen der zunehmenden Digitalisierung in der Industrie rief RWE Power/Generation das Projekt Big Data@RWE-Generation ins Leben. Darin soll untersucht werden, ob sich aus dieser immer mehr an Bedeutung gewinnenden Technologie, bzw. deren technologischen Möglichkeiten, auch Effizienzsteigerungen für den Betrieb und die Instandhaltung von Kraftwerken ableiten lassen. Das Projekt Big Data@RWE-Generation wird dabei auf die gesamte Wertschöpfungskette der RWE Power und der RWE Generation angewendet...
Building a data science project from scatch: an analysis of Berlin rental prices (EN)
Jekaterina Kokatjuhha, Data Analyst (Business Excellence), Zalando SE
17:45 - 18:15
Research Engineer
Building a data science project from scatch: an analysis of Berlin rental prices (EN)This talk is about how to design a good data science project from scratch based on a real world dataset. As a showcase project we analyze the rental prices for apartments in Berlin.This talk will guide you through all the steps of a short-term data science project: motivation, extraction of data from the web, cleaning and engineering of features using external APIs, storytelling, and building machine learning models...
Cryptocurrency - how to predict a coins’ movement with Machine Learning and Advanced Analytics (EN)
Thomas Blomberg, Senior Product Manager, TIBCO | Joseph Gade Senior Solution Consultant, TIBCO
17:45 - 18:15
Blockchain
Cryptocurrency - how to predict a coins’ movement with Machine Learning and Advanced Analytics (EN)Machine Learning has become an essential part of big data analytics. But how do you start using ML and keep your visual data discovery experience easy to use at the same time? In this session we will use advanced analytics to analyse cryptocurrencies by starting with a cryptocurrency Spotfire analysis and then combine it with ML. The result is a much more powerful analysis that allows us to gain more insights and answer more questions out of our data.
18:00
18:15
18:30
18:45
19:00
Party @ Stiglerie München
19:00 - 00:00
Party @ Stiglerie München
19:00 - 00:00
Party @ Stiglerie München
19:00 - 00:00
19:15
19:30
19:45
20:00
20:15
20:30
20:45
21:00
21:15
21:30
21:45
22:00
22:15
22:30
22:45
23:00
23:15
23:30
23:45

data.stage

festival.stage

alterna.stage

data.stage festival.stage alterna.stage
09:45
Begrüßung / Introduction
Alexander Thamm, Dr. Carsten Bange
09:45 - 10:00
10:00
10:15
10:30
Break
10:30 - 10:45
Break
10:30 - 10:45
Break
10:30 - 10:45
10:45
11:00
11:15
Analytics on Azure - Architekturvarianten und Praxisfälle (DE)
Dr. Andreas Stadie, Head of Analytics, EnBW AG und Yello Strom
11:15 - 11:45
Cloud
Analytics on Azure - Architekturvarianten und Praxisfälle (DE)Seit 20 Jahren rücken Data Science und Informatik kontinuierlich enger zusammen. Der aktuelle Meilenstein dieser Konvergenz sind die statistisch analytischen Fähigkeiten der Cloud Systeme. Es gibt bereits ein Reihe von Nutzungsmöglichkeiten der analytischen Cloud Services mit verschiedenen Vor- und Nachteilen. In dem Vortrag werden einige Praxisfälle aus dem täglichen Massenkundengeschäft aufgegriffen und deren Implementierung in der Azure Cloud erläutert.
11:30
11:45
12:00
12:15
Lunch
12:15 - 13:30
Lunch
12:15 - 13:30
Lunch
12:15 - 13:30
12:30
12:45
13:00
13:15
13:30
Best Practices: Warum Blockchain und insbesondere die kognitive CortexPlatform die Datenwelt revolutionieren (DE)
Dr. Georg Loepp, Chief Visionary Officer, Cegeka Deutschland GmbH & Jan Buss, CEO, Cortex
13:30 - 15:00
Workshop
Best Practices: Warum Blockchain und insbesondere die kognitive CortexPlatform die Datenwelt revolutionieren (DE)Als einzige Datenbank bietet die CortexDB – als Kern der CortexPlatform – vollautomatisch die höchste Normalform (6. Normalform) als Index über alle Inhalte aller Datensätze. Zu jedem Wert ist somit bekannt wo und wie häufig dieser Inhalt auftritt. Ergänzend dazu sind alle zeitlichen Verläufe einer Information erkenn- und nachvollziehbar. ...
Daten Party oder Spaßbremse – Alles eine Frage der Architektur (DE)
Jens Schnettler, Senior Manager, Woodmark Consulting AG
13:30 - 15:00
Workshop
Daten Party oder Spaßbremse – Alles eine Frage der Architektur (DE)Ein Realitätscheck aus dem Big Data- und Advanced Analytics Umfeld. Die fortschreitende Digitalisierung führt zu neuen Anforderungen an analytische Informationssysteme unserer Zeit...
13:45
14:00
14:15
14:30
14:45
15:00
Coffee Break
15:00 - 15:30
Coffee Break
15:00 - 15:30
Coffee Break
15:00 - 15:30
15:15
15:30
Hans im Datenglück. Von Mystery Shopping, Social Media & Geodaten – smarte Datenanalysen mit Qlik Sense (DE)
Denys Dertwinkel, Leiter Controlling, Hans im Glück Franchise GmbH & Stefanie Greineder, Operatives Controlling, Hans im Glück Franchise GmbH
15:30 - 16:00
Analytics & Visualization
Hans im Datenglück. Von Mystery Shopping, Social Media & Geodaten – smarte Datenanalysen mit Qlik Sense (DE)Der Besuch eines Burgergrills als besonderer Moment des Glücks. Das ist der Maßstab, an dem Hans im Glück seinen Erfolg misst. Daher setzt Hans im Glück Qlik Sense ein, um sämtliche Daten zum Kundenerlebnis im Blick zu behalten und auszuwerten. Während der Präsentation zeigt Denys Dertwinkel, wie Daten zu Mystery Shoppern, Social Media, den Restaurants und Geoinformationen zu KPIs verdichtet werden.
15:45
16:00
Datendemokratisierung @ Telefónica Deutschland (DE)
Laura Velikonja, Data Scientist, Telefónica Deutschland GmbH & Co. OHG
16:00 - 16:30
Analytics & Visualization
Datendemokratisierung @ Telefónica Deutschland (DE)Vor über einem Jahr hat der Vorstand von Telefónica Deutschland eine ungewöhnliche Entscheidung getroffen: alle Mitarbeiter sollen auf den gesammelten Datenbestand des Unternehmens zugreifen können. Das Analytical Insights Center (AIC) ermöglicht so neue Formen des Arbeitens und Entscheidens in der digitalen Welt. Nun geht der Bereich Business Analytics & Artificial Intelligence der Telefónica Deutschland den konsequenten nächsten Schritt in dieser Entwicklung: von der Datendemokratisierung zur Analytics Demokratisierung...
16:15
16:30
DATA - PREP - GO! Vorbereitung und Analyse so einfach und begeisternd wie Lego (Sie werden Bauklötze staunen…) (DE)
Oliver Linder, Sales Consultant Team Lead, Tableau Software
16:30 - 17:00
Analytics & Visualization
DATA - PREP - GO! Vorbereitung und Analyse so einfach und begeisternd wie Lego (Sie werden Bauklötze staunen…) (DE)Aus wie vielen Steinen besteht das Taj Mahal? Von welcher Farbe gibt es die meisten Lego Steine? Wie viele Lego Sets gibt es? Diese und andere spannende Fragen beantwortet Oliver Linder in seinem Vortrag. Er zeigt ihnen wie man mit Tableau, umfangreiche und komplexe Datensets blitzschnell aufbereiten und analysieren kann.
16:45
17:00
Break
17:00 - 17:15
Break
17:00 - 17:15
Break
17:00 - 17:15
17:15
Condition Based Monitoring (DE)
Rene Ahlgrim, Data Scientist, Zeppelin GmbH
17:15 - 17:45
Predictive Manufacturing
Condition Based Monitoring (DE)Erster Use Case (Prototyp) bei Zeppelin. Use Case Zündkerze --> Wie können wir die Ausfallzeiten von Blockheizkraftwerken (BHKW´s) reduzieren? Hierzu wurden die Daten analysiert und die wesentliche Counter bestimmt die Ausfälle frühzeitig detektierbar machen...
Open Source vs. Kommerzielle Software - Vorteile, Nachteile, Integrationsmöglichkeiten (DE)
Dr. Sebastian Derwisch, Data Scientist, BARC GmbH
17:15 - 17:45
Data Project Implementation
Open Source vs. Kommerzielle Software - Vorteile, Nachteile, Integrationsmöglichkeiten (DE)Open Source Sprachen zur Entwicklung von Advanced Analytics Modellen haben ihre Stärken vor allem in der Datenaufbereitung und der Modellierung. Hier ist der Funktionsumfang groß, die Community oft sehr aktiv und die Flexibilität, die eine Programmiersprache bietet, wichtig. Allerdings gibt es Probleme bei der Performanz, die Iterationszyklen in der Prototypisierung verlangsamen können...
17:30
17:45
Big Data @Maintenance: Neue Wege bei den Instandhaltunsprozessen von konventionellen Kraftwerken (DE)
Natividad Jordan Escalona, Officer for Research & Development, RWE Power AG
17:45 - 18:15
Predictive Manufacturing
Big Data @Maintenance: Neue Wege bei den Instandhaltunsprozessen von konventionellen Kraftwerken (DE)Im Rahmen der zunehmenden Digitalisierung in der Industrie rief RWE Power/Generation das Projekt Big Data@RWE-Generation ins Leben. Darin soll untersucht werden, ob sich aus dieser immer mehr an Bedeutung gewinnenden Technologie, bzw. deren technologischen Möglichkeiten, auch Effizienzsteigerungen für den Betrieb und die Instandhaltung von Kraftwerken ableiten lassen. Das Projekt Big Data@RWE-Generation wird dabei auf die gesamte Wertschöpfungskette der RWE Power und der RWE Generation angewendet...
18:00
18:15
18:30
18:45
19:00
Party @ Stiglerie München
19:00 - 00:00
Party @ Stiglerie München
19:00 - 00:00
Party @ Stiglerie München
19:00 - 00:00
19:15
19:30
19:45
20:00
20:15
20:30
20:45
21:00
21:15
21:30
21:45
22:00
22:15
22:30
22:45
23:00
23:15
23:30
23:45

data.stage

festival.stage

alterna.stage

data.stage festival.stage alterna.stage
09:45
Begrüßung / Introduction
Alexander Thamm, Dr. Carsten Bange
09:45 - 10:00
10:00
Ten Key Principles on how to Transform a Global Company into a Data Driven Leader (EN)
Dr. Alexander Borek, Head of Smart Data & Analytics, Volkswagen AG & Alexander Thamm, CEO, Alexander Thamm GmbH
10:00 - 10:30
Keynote
Ten Key Principles on how to Transform a Global Company into a Data Driven Leader (EN)Each Data Transformation Journey is different, but there are some solution patterns that can help in traditional industries. The presentation will explore the following questions on how to drive the change towards a truly data driven enterprise...
10:15
10:30
Break
10:30 - 10:45
Break
10:30 - 10:45
Break
10:30 - 10:45
10:45
Decision Automation: How to get there and what to consider (EN)
Dr. Carsten Bange, Founder and CEO, BARC GmbH
10:45 - 11:15
Data Strategy & Organization
Decision Automation: How to get there and what to consider (EN)The increased use of data science and machine learning leads to more models being used in operational processes. Models are also increasingly adopting decisions here, especially when the speed of decision-making or the data basis is no longer manageable for people. But at the moment, however, this is only occasionally and almost coincidental, because many companies lack a strategy to control this change...
Building a Central Hive Metastore in a Multi-Account AWS Cloud Environment (EN)
Raffael Dzikowski, Big Data Engineer, Scout24 Group
10:45 - 11:15
Cloud
Building a Central Hive Metastore in a Multi-Account AWS Cloud Environment (EN)One of the central challenges when providing a Data Lake architecture in a multi-account Cloud setup on AWS consists in offering a consistent, familiar, and easy-to-use access mechanism to it which ideally hides all the nitty-gritty details of varying data formats and data sources, while at the same time making the data available for analysis in a convenient way. A proven abstraction that meets these requirements is a set of relations (tables) that enable analyses using the well-established Structured Query Language (SQL)...
Identification of patterns in TV consumption Seven One Media GmbH (EN)
Igor Rotin, Senior Data Mining Manager, SevenOne Media GmbH
10:45 - 11:15
Pattern Recognition & Deep Learning
Identification of patterns in TV consumption Seven One Media GmbH (EN)The prognosis of TV consumption of target groups related to program genres is the planning and steering basis for many continuative applications for a TV station. This includes content topics for programming as well as the seasonal placement of specific programs. In addition the changing media usage due to the rapid increase of internet distribution has also influenced TV consumption...
11:00
11:15
From 5 to 90 - Scaling a Big Data Team in 2 years (EN)
Joachim Bürkle, Head of and Product Owner, DB Systel GmbH (ZERO.ONE.DATA)
11:15 - 11:45
Data Strategy & Organization
From 5 to 90 - Scaling a Big Data Team in 2 years (EN)ZERO.ONE.DATA, a Corporate Startup of the DB Systel Innovation & New Venture Business Area, is focusing on Big Data (DataOps, Data Intelligence, Data Projects and Business Services). The presentation will describe how ZERO.ONE.DATA has grown from 5 initial Team Members to more than 90 Members within just 2 years. Difficulties in scaling agile Organizations beyond 10 Members and beyond 40-50 Members, will be addressed as well as the impact on the work of a Product Owner...
Deep Learning with medical images (EN)
Dr. Marie Piraud, Senior Researcher, TU München
11:15 - 11:45
Pattern Recognition & Deep Learning
Deep Learning with medical images (EN)In this talk, I will give an introduction of Deep learning in the medical field, and in particular its application to the processing of medical images. Medical computer Vision is a field of Data Science which has its own specificities and challenges, such as data scarceness and variability, and where the black-box aspect is a big drawback. As a use case, we will present the work carried out in the Image-Based Biomedical Modeling research group of the TU Munich...
11:30
11:45
What is the big in (Big) data? And how lean can your data be... (EN)
Dat Tran, Head of Data Science,  idealo.de
11:45 - 12:15
Data Strategy & Organization
What is the big in (Big) data? And how lean can your data be... (EN)Deep Learning, Artificial Intelligence, Tensorflow, Spark, Flink, Big Data, Smart Data, Hadoop, IoT, Agile, Cloud… There has been a lot of hype around those buzzwords and no they are not names of any Pokemons. In this talk, I want to make some sense out of the buzz nowadays. I will share some of my war stories as well as my own experiences in building up a data science team at the largest price comparison service in Germany.
Building an Operational Data Layer for the Real Time demands of Cloud based applications (EN)
Negib Marhoul, Solution Engineer, DataStax Inc.
11:45 - 12:15
Cloud
Building an Operational Data Layer for the Real Time demands of Cloud based applications (EN)Come and learn the challenges faced with building new cloud based applications and the demands they put on backend systems. Learn from DataStax how our customers use an Operational Data Layer to provide real time analytics and scoring on contextual data, keeping it always on, distributed and scalable. While offloading the backend systems.
Understanding furnishing styles from images (EN)
Christian Nietner, Founder & CTO, RoomAR
11:45 - 12:15
Pattern Recognition & Deep Learning
Understanding furnishing styles from images (EN)RoomAR is a new bleeding edge software product that is targeting retailers and manufacturers in the furniture and home furnishing industry. The software visualizes virtual products in the real world using the RoomAR augmented reality mobile app. The user experience is enriched by personalized product recommendations. With the help of deep learning and computer vision algorithms, the personal interior design style and the actual living situation of users are considered...
12:00
12:15
Lunch
12:15 - 13:30
Lunch
12:15 - 13:30
Lunch
12:15 - 13:30
12:30
12:45
13:00
13:15
13:30
Blockchain - Status Quo and Potentials (EN)
Attendees Thomas Schmiedel , Data Scientist, Data Reply & Sebastian Heinz, CEO, Statworx & Marco Plaul, Data Scientist, Alexander Thamm GmbH
13:30 - 14:15
Blockchain - Status Quo and Potentials (Panel)
Blockchain - Status Quo and Potentials (EN)The blockchain technology has developed into one of the most important disruptors of our times, with potential for changing the economy as a whole in the near future. We will therefore discuss the following questions in the panel...
A 60m Data Challenge: Can You Make It? (EN)
Alexandre Combessie, Data Scientist, Dataiku
13:30 - 15:00
Workshop
13:45
14:00
14:15
data.networking(1) (EN)
Anna Milaknis, Desing Thinkerin
14:15 - 15:00
Networking
data.networking(1) (EN)„Share your passion for data“ and meet 10 exciting data people in 30 minutes. Bring your business cards and prepare a short introduction about yourself. You’ll spend three minutes exchanging cards and information with a fellow attendee. When the chime sounds, you’ll move on to the next attendee.
14:30
14:45
15:00
Coffee Break
15:00 - 15:30
Coffee Break
15:00 - 15:30
Coffee Break
15:00 - 15:30
15:15
15:30
Data Lake Production @Audi - Architecture, Technologies & Organisation (EN)
Christoph Kreibich, Data Scientist, Audi AG
15:30 - 16:00
Data & AI in Automotive I
Data Lake Production @Audi - Architecture, Technologies & Organisation (EN)Data is an elementary part of the digitalization of production at Audi AG. In order to be able to store and analyze data from vehicle and component manufacturing and logistics in an international production network, a central data lake was set up. The Audi Analytics Platform collects data from all business areas and makes it available for cross-functional analyses...
The Death of Data Science - Towards AI fueled Machine Learning Automation (EN)
Sebastian Heinz, CEO, STATWORX
15:30 - 16:00
Machine Learning & Predictive Analytics
The Death of Data Science - Towards AI fueled Machine Learning Automation (EN)Data Science, machine learning and AI are currently disrupting industries worldwide. However, recent advances in AI as well as the ongoing progress on automation of many data science and machine learning related workflows will disrupt and most likely wipe out data science itself in the future. The talk will give you an understandable overview on state of the art algorithms in the field of AI based ML automation and features practical examples of applying automated machine learning.
15:45
16:00
How data connects cultures, markets, business areas and just by that generates massive potentials (EN)
Dr. Stefan Meinzer, Head of regional analytics services for EMEA, BMW AG
16:00 - 16:30
Data & AI in Automotive I
How data connects cultures, markets, business areas and just by that generates massive potentials (EN)The national sales companies of the automotive industry have the closest contact to the dealers and the customers in the automotive industry. They push on sales and customer interaction. However, due to intercultural differences or language barriers the development of business models is still challenging and thereby requires high human efforts. On the other hand, there is one language that is unique around the world – DATA. Based on a concrete use case, we explain how the BMW Group uses the existing international knowledge to define new data driven business models that will drive customers’ centricity to the next level. With latest machine learning methodologies, skilled data scientists and international automotive experts we let data bundle the strengths to shape the future.
Big Data Predictive Monitoring meets Blockchain (EN)
Francesco Sbaraglia, Big Data Engineer / Manager, Data Reply & Thomas Schmiedel, Data Scientist, Data Reply
16:00 - 16:30
Machine Learning & Predictive Analytics
Big Data Predictive Monitoring meets Blockchain (EN)One of the most hyped topics about Big Data is Predictive Maintenance. In production, for example, sensor data from machines are analyzed so that the next scheduled maintenance can be accurately predicted in order to avoid downtime costs. Can this same principle also be transferred to IT infrastructures? That\\\\\\\'s what Big Data Predictive Monitoring does. It collects metrics, at various levels of IT systems (e.g., processor, memory, network, ...). The detailed metadata are stored using Hadoop clusters and Timeseries Database. Ultimately, this monitoring serves not only as predictive maintenance, but also to optimize performance and to predict crashes. Unlike from Machines,
16:15
16:30
Predictive Control of R&D Projects in Manufacturing by Analyzing the Project Data Base (EN)
Dr. Max Köhler, Data Scientist, Continental AG
16:30 - 17:00
Data & AI in Automotive I
Predictive Control of R&D Projects in Manufacturing by Analyzing the Project Data Base (EN)R&D Projects in manufacturing are risky! Money must be invested even though the outcome is hard to be determined in advance and possible earnings reveal themselves many months or even years after the project has been finished. Project control often looks for KPIs measuring the state of the project at a given point in time. This approach neither looks ahead nor does it allow root cause analysis...
Advanced Demand Forecasting through Predictive Analytics at BASF (EN)
Benjamin Priese, Data Science Sen. Manager, Advanced Business Analytics, BASF SE & Dr. Thomas Christ, Chief Data Scientist, prognostica GmbH
16:30 - 17:00
Machine Learning & Predictive Analytics
Advanced Demand Forecasting through Predictive Analytics at BASF (EN)Reliable forecasts are a key factor for an efficient and effective management of supply chains. A new forecasting framework for Demand Planning has been developed and implemented successfully at BASF based on advanced predictive analytics methods and sophisticated information technology...
16:45
17:00
Break
17:00 - 17:15
Break
17:00 - 17:15
Break
17:00 - 17:15
17:15
Solving real world data problems faster with Search and Semantics (EN)
Daniel Holgate, Senior Sales Engineer, MarkLogic Corporation
17:15 - 17:45
Semantics
Solving real world data problems faster with Search and Semantics (EN)How can data be better modelled to reflect the real world? Sometimes it takes a combined approach...
17:30
17:45
Building a data science project from scatch: an analysis of Berlin rental prices (EN)
Jekaterina Kokatjuhha, Data Analyst (Business Excellence), Zalando SE
17:45 - 18:15
Research Engineer
Building a data science project from scatch: an analysis of Berlin rental prices (EN)This talk is about how to design a good data science project from scratch based on a real world dataset. As a showcase project we analyze the rental prices for apartments in Berlin.This talk will guide you through all the steps of a short-term data science project: motivation, extraction of data from the web, cleaning and engineering of features using external APIs, storytelling, and building machine learning models...
Cryptocurrency - how to predict a coins’ movement with Machine Learning and Advanced Analytics (EN)
Thomas Blomberg, Senior Product Manager, TIBCO | Joseph Gade Senior Solution Consultant, TIBCO
17:45 - 18:15
Blockchain
Cryptocurrency - how to predict a coins’ movement with Machine Learning and Advanced Analytics (EN)Machine Learning has become an essential part of big data analytics. But how do you start using ML and keep your visual data discovery experience easy to use at the same time? In this session we will use advanced analytics to analyse cryptocurrencies by starting with a cryptocurrency Spotfire analysis and then combine it with ML. The result is a much more powerful analysis that allows us to gain more insights and answer more questions out of our data.
18:00
18:15
18:30
18:45
19:00
Party @ Stiglerie München
19:00 - 00:00
Party @ Stiglerie München
19:00 - 00:00
Party @ Stiglerie München
19:00 - 00:00
19:15
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19:45
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21:00
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23:45

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