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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.

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  • Montag
    21.06.
  • Dienstag
    22.06.
  • Mittwoch
    23.06.
09:00 - 10:00
KeyMo
KEYNOTE und Eröffnung: What is work & What is human – in a superhuman future

For the work we do in the long-term-vision-labs and strategy team for the Technology & Innovation board area at SAP is one of the playgrounds for the title question. These topics are good, because they generate exiting and abundant questions, that we believe should be asked by everyone.

How does the future work, the mechanics of change? What is the future of human work and our interactions with machines and each other? Is industrialization of space and 3d printed organs really a “thing” and how…

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Martin Wezowski
Track: Keynote
Vortrag: KeyMo
10:00 - 10:10
Short Break
Short Break
10:10 - 10:50
Mo 2.1
Daily regression in an enterprise data warehouse

Over the last few decades, ETL and specially Datawarehouse testing has been gaining quite a bit of traction. The reason for that traction? The modern enterprise's dependency on data. This dependency calls for the right testing strategy to ensure the quality and correctness of the provided data. Further on the drive to lower 'time to data' and overall costs is putting high pressure on Test specialists to increase efficiency in this area. In this presentation I want to show you our journey to…

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Bernhard Frauneder
10:10 - 10:50
Mo 3.1
The need for a unified big data architecture

Big data is not the biggest change in the IT industry but data usage. To become more data driven and to succeed with their digital transformation, organizations are using their data more extensively to improve their business and decision processes. Unfortunately, it is hard for current data delivery systems to support new styles of data usage, such as data science, real-time data streaming analytics, and managing heavy data ingestion loads. This session discusses a real big-data-ready data…

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Rick van der Lans
10:50 - 11:20
Break
Break
11:20 - 12:30
Mo 1.2
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…

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Martin Fadler, Christine Legner
11:20 - 12:30
Mo 2.2
Distributed databases in a microservice environment

Using distributed databases across various microservices will be explained based on a research project example. The presentation elaborates of how to achieve data consistency across microservices, how to communicate using message brokers, how to scale the microservices and achieve high application availability. Container virtualization and orchestration are technology basis for the solution. The project example shows of how to build an Artificial Intelligence (AI) solution – as a service!

Target…

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Matthias Braun
11:20 - 12:30
Mo 3.2
Data virtualization in real life projects

Data virtualization is being adopted by more and more organization for different use cases, such as 360 degrees customer views, logical data warehouse, democratizing data, and self-service BI. The effect is that knowledge about this agile data integration technology is available on how to use it effectively and efficiently. In this session lessons learned, tips and tricks, do's and don'ts, and guidelines are discussed. And what are the biggest pitfalls? In short, the expertise gathered from…

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Rick van der Lans
12:30 - 14:00
Lunch Break
Lunch Break
14:00 - 15:30
Mo 3.3
DataOps: using data fabric and a data catalog for continuous development of data assets

As the data landscape becomes more complex with many new data sources, and data spread across data centres, cloud storage and multiple types of data store, the challenge of governing and integrating data gets progressively harder. The question is what can we do about it? This session looks at data fabric and data catalogs and how you can use them to build trusted re-usable data assets across a distributed data landscape.

Target Audience: CDO, Data Engineer, CIO, Data Scientist, Data Architect,…

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Mike Ferguson
14:40 - 14:50
Short Break
Short Break
14:50 - 15:30
Mo 1.4
Insights to action: ABB's journey to data driven decisions

How do you enable digital transformation and create value through analytics?

Building a global analytics function across a diverse application landscape incl. SAP and multiple data sources provides many challenges. See how ABB successfully managed this journey and now enjoys the benefits of operational analytics globally, a shift in mindsets and a more data driven way of working.

You will also discover the impact of key technologies used (Change-Data-Capture, Automation & AI) and see real…

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Mircea Zamfir, Feridun Ozmen
14:50 - 15:30
Mo 2.4
Building a data culture with people and ideas that matter

A successful data culture brings together people from across the business to collaborate, share and learn from each other about data, analytics and the business value data can hold. In this session I share my suggestions for bringing together your most talented data people so your organization can gain more value from their skills and the data assets you invested in.

Come with an open mind and leave with tips, tricks and ideas to get started straight away.

Target Audience: Data practitioners,…

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Eva Murray
15:30 - 16:00
Break
Break
16:00 - 17:10
Mo 3.5
No more metadata, let's talk context and meaning

Metadata is a long-time favourite at conferences. However, most attempts to implement real metadata solutions have stumbled. Recent data quality and integrity issues, particularly in data lakes, have brought the topic to the fore again, often under the guise of data catalogues. But the focus remains largely technological. Only by reframing metadata as context-setting information and positioning it in a model of information, knowledge, and meaning for the business can we successfully implement…

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Barry Devlin
16:00 - 17:10
Mo 4.5
AI factory and metadata driven data ingestion at ERGO

In this session, the ERGO Group, one of Europe's leading insurance companies, presents their AI Factory for development and operationalization of AI models. The session gives an architectural overview of the AI Factory's components. Furthermore, it explains how cloud-native technologies like Openshift and AWS Cloud Services aided in moving towards a data driven organization. A deep dive into the AI Factory's data ingestion process shows how metadata-driven data ingestion supports Data Governance…

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Felix Wenzel, Christian Kundruß, Lukas Hestermann
17:10 - 17:30
Short Break
Short Break
18:15 - 19:15
Welcome Reception
Welcome Reception

Digital Welcome Reception

09:45 - 10:00
Short Break
Short Break
10:00 - 10:40
Di 4.1
End-to-End-Use Case: Metadata Management & DWH

Like many companies, the 3 banks face the challenge of implementing data governance. With an end-to-end approach for metadata – from the business definition to the DWH implementation – a basis was created for this. The use cases 'IT requirements', 'data quality' and 'data definitions' were the focus of the resource-saving project. The target groups for the metadata are primarily the LoB, especially risk management, but also IT.

Target Audience: Data Governance Manager, Risk Manager, Data Quality…

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Clemens Bousquet, Lisa Müller
10:40 - 11:10
Break
Break
12:20 - 12:30
Short Break
Short Break
13:00 - 14:00
Lunch Break
Lunch Break
14:40 - 14:50
Short Break
Short Break
14:50 - 15:30
Di 2.4
From BI to AI & analytics industrialization

I will show the journey that Tires took from its first attempts to extend their BI services for analytics to operate a mission critical industrialization environment which runs several AI projects. Beneath the problems and obstacles that were taken I will also explain the decisions that were taken and show the industrialization environment which was created. I also will explain why it was necessary to have such an environment instead of making use of classical BI tools.

Target Audience: Project…

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Dubravko Dolic
14:50 - 15:30
Di 3.4
Integration of SAP data into a common data model

In the past, data was often stored in a monolithic data warehouse. Recently, with the advent of big data, there has been a shift to work directly with files. The challenge therefore arises in data management and storing metadata information. In this presentation, I will show how SAP (ERP or BW) data can be extracted using SAP Data Intelligence (ODP framework) and stored along with their metadata information. These data are stored in a Common Data Model (CDM) format and can be easily integrated…

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Julius von Ketelhodt
15:30 - 16:00
Break
Break
16:00 - 17:10
Di 2.5
Quantifying the impact of customer experience improvements on churn via causal modeling

Quantifying the impact of customer experience (CX) improvements on the financials is crucial for prioritizing and justifying investments. In telecommunication as well as other subscription-based industries, churn is one of or the most important financial aspects to take into account. The presented approach shows how the churn impact of CX improvements – measured via Net Promoter Score (NPS) – can be estimated based on structural causal models. It makes use of algorithms for causal discovery and…

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Björn Höfer
17:20 - 18:10
Special Keynote
SPECIAL KEYNOTE: Lessons from the Racetrack with Gary Paffett, Championship Winning Racing Driver
Gary Paffett
Track: Keynote
Vortrag: Special Keynote
09:00 - 09:40
Mi 1.1
Integrating SAP data into a modern analytics warehouse on Google Cloud in an automated fashion

Transforming an organization to become more data driven usually presents a set of technological challenges. In this session you will learn how to integrate existing applications data in real time to achieve a useful critical mass of explorable data.

Target Audience: CTOs, CIOs, CDOs, data engineers, data modelers, data analysts, data scientists
Prerequisites: General understanding of data in the context of the enterprise
Level: Basic

Extended Abstract:
'Data is the new oil' these days many…

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Matthias Krenzel
09:00 - 10:30
Mi 4.1
Is there life beyond hadoop – should data lakes be drained?

The past year or two has seen major changes in vendor support for the extended Hadoop ecosystem, with withdrawals, collapses, and mergers, as well as de-emphasis of Hadoop in marketing. Some analysts have even declared Hadoop dead. The reality is more subtle, as this session shows, through an exploration of Hadoop's strengths and weaknesses, history, current status and prospects. Discussion topics include plans for initiating new Hadoop projects and what to do if you have already invested,…

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Barry Devlin
09:40 - 09:50
Short Break
Short Break
09:50 - 10:30
Mi 2.2
Quality whisperer – self-learning AI for production quality

ZF plant Saarbrücken, Germany, manufactures around 11,000 transmissions per day. With 17 basic transmission types in 700 variants, the plant manages a large number of variants. Every transmission consists of up to 600 parts. An AI project was started to get reliable + fast results on root cause discovery. Speed is important because production runs 24 hours/7 days a week. The target is to reduce waste in certain manufacturing domains by 20%. The key success factor is the fast detection mechanism…

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Britta Hilt
10:30 - 11:00
Break
Break
11:00 - 12:10
Mi 4.3
Data science workbenches and machine learning automation – new technologies for agile data science

This session looks at how data science workbenches and machine learning automation tools can help business analysts to become data scientists and so meet the demand of business.

Target Audience: CDO, Head of Analytics, Data Scientist, Business Analysts, CIO
Prerequisites: Basic understanding of Data Science
Level: Advanced

Extended Abstract:
The demand for analytics is now almost everywhere in the business. Analytics are needed in sales, marketing and self-service, finance, risk, operations,…

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Mike Ferguson
12:10 - 12:25
Short Break
Short Break
12:25 - 13:10
KeyMi
KEYNOTE: Corporate IT Is a Theater Piece - What Role Are You Playing?

The engagement of IT staff in organizations has been done for decades via a single function or department. Whatever title it bears, the single counter IT takes care of everything under the digital sun. This model generates unhealthy behaviors in the IT ranks that are detrimental to the enterprises that need digital to operate, evolve, transform —or survive. 

Drawing a parallel with a more mature industry, the current distribution of roles is analyzed and compared. It shows that the standard…

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R.M. Bastien
Track: Keynote
Vortrag: KeyMi
13:10 - 14:30
Lunch Break
Lunch Break
14:30 - 18:10
Mi 4.4
Best practices in DataOps for analytics

Analytics team are struggling to create, publish, and maintain analytics to meet demand. Many analytics projects fail to meet expectations and deliver value. DataOps is the new approach combining tools and approaches to simplify the development of analytics and ensuring high quality data. DataOps shortens the life cycles, reduces technical debit and increases analytics success. This session covers the best practices for the analytics team to deliver DataOps.

Target Audience: Data scientists,…

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Deanne Larson
15:40 - 16:10
Break
Break
16:10 - 16:50
Mi 3.5
Machine learning raises industry 4.0 to the next level

How is machine learning used in the real world? How did our customer Liebherr mitigate the problem of unreliable suppliers, therefore making their manufacturing process more efficient? How can our customers work their way through thousands of documents, quickly identifying the relevant ones? In this talk, Data Scientist Björn Heinen will elaborate on his past and current projects in the manufacturing industry by explaining how tangible customer problems have been solved using classical machine…

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Björn Heinen
Track: IoT
Vortrag: Mi 3.5
16:50 - 17:00
Short Break
Short Break

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