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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).
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Thema: Data Strategy
- Montag
20.06. - Dienstag
21.06. - Mittwoch
22.06.
Fast jeder Beitrag zu moderner BIA fängt mit dem Satz an 'Noch nie wurden so viele Daten wie heute gesammelt'. Es gilt als Daumenregel: Willst du Machine Learning machen, musst du viele Daten sammeln. Da wird man schon fast zum Spielverderber, wenn man das Thema Datenlöschungen anspricht. Erfahren Sie, warum es trotzdem wichtig ist, dieses eher unliebsame Thema als Spezialfall einer Data Governance auf die Tagesordnung zu setzen.
Zielpublikum: CDOs, CISOs, IT-Leiter, Datenschutzverantwortliche
Voraussetzungen: Grundlegendes Verständnis von Datenintegrationen und Datenschutz
Schwierigkeitsgrad: Einsteiger
Christian Schneider ist der Director Data & Analytics bei der QuinScape GmbH. Als Consultant und Projektleiter war er langjährig in internationalen Großprojekten tätig und kennt die vielfältigen Herausforderungen unterschiedlichster Integrations- und Analytikszenarien aus der praktischen Arbeit. Als Speaker und in Publikationen beleuchtet er die Aspekte des Aufbaus von nachhaltigen Dateninfrastrukturen mit einem im späteren Betrieb überschaubaren Kostenrahmen durch eine zielorientierte Data Governance.
The setup of a decentral function-based data governance requires time, shapes a continuous learning organisation and grows data capabilities and competence in the functions. Through these means a sustainable data culture is established and anchored, which plays a particular role in realising the strategic corporate goals, such as the digital transformation of processes.
Target Audience: Data Governance Manager, Data Passionist, CDO, CIO, Data Analytics Specialist
Prerequisites: Basic knowledge of the Data Governance
Level: Basic
Leonie Frank has worked in data management for the past 10 years for companies like Google and Swarovski and supported others in her role as a consultant. Her passion is to drive activities related to data management not only to roles and responsibilities, standards and guidelines but also to data architecture, data quality and data performance. Leonie’s goal is to enable teams that help to increase data maturity allowing to safeguard and utilise data as a company asset. She holds a degree in International Business Administration, a master in International Political Economy from the University of Warwick in the UK, a certificate in Statistics and one in Applied Information Technology from ETH in Switzerland. Leonie lives in Zurich and loves fine cooking and dining as well as mountaineering.
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Missing data leadership, lack of vision, data-unliterate business units, data in silos, no data- and analytics-governance - The symptoms of a missing data strategy are unmistakable. Whilst organizations strive to exploit the benefits promised from data & analytics, corporate well thought data strategies are rather an exception than rule. We would like to exchange best practices and experiences for designing & implementing sustainable yet pragmatic data strategies for organizations.
Target Audience: Practitioners for data strategy consulting, (Data-) decision makers in organizations, Data leaders, BI & AI team leaders
Prerequisites: Experience and knowledge in the area of analytics, BI or AI; data use cases
Level: Basic
Extended Abstract:
TOC draft
- Overview elements of a data strategy
- Typical initial situations in organizations
- Toolkits and methodologies when designing data strategies
- Exchange of experiences & best practices
Jens is a seasoned Data Scientist and Strategist with more than 15 years of professional experience in generating business value from data using Analytics, Data Science & AI. He led many data projects with measurable success for renowned international clients. Today, he helps organizations to design and implement data strategies for their digital transformation journeys.
Boris and his team are working passionately to drive the adoption of solutions and processes that enable people to make healthy, data driven decisions. These approaches cover the entire data value added chain starting from raw data to sophisticated Business Intelligence Applications or AI solutions based on modern data science.
The data lakehouse is the new popular data architecture. In a nutshell, the data lakehouse is a combination of a data warehouse and a data lake. It makes a lot of sense to combine them, because they are sharing the same data and similar logic. This session discusses all aspects of data warehouses and data lakes, including data quality, data governance, auditability, performance, historic data, and data integration, to determine if the data lakehouse is a marketing hype or whether this is really a valuable and realistic new data architecture.
Target Audience: Data architects, enterprise architects, solutions architects, IT architects, data warehouse designers, analysts, chief data officers, technology planners, IT consultants, IT strategists
Prerequisites: General knowledge of databases, data warehousing and BI
Level: Basic
Extended Abstract:
The data lakehouse is the new kid on the block in the world of data architectures. In a nutshell, the data lakehouse is a combination of a data warehouse and a data lake. In other words, this architecture is developed to support a typical data warehouse workload plus a data lake workload. It holds structured, semi-structured and unstructured data. Technically, in a data lake house the data is stored in files that can be accessed by any type of tool and database server. The data is not kept hostage by a specific database server. SQL engines are also able to access that data efficiently for more traditional business intelligence workloads. And data scientists can create their descriptive and prescriptive models directly on the data.
It makes a lot of sense to combine these two worlds, because they are sharing the same data and they are sharing logic. But is this really possible? Or is this all too good to be true? This session discusses all aspects of data warehouses and data lakes, including data quality, data governance, auditability, performance, immutability, historic data, and data integration, to determine if the data lakehouse is a marketing hype or whether this is really a valuable and realistic new data architecture.
Rick van der Lans is a highly-respected independent analyst, consultant, author, and internationally acclaimed lecturer specializing in data architectures, data warehousing, business intelligence, big data, and database technology. He has presented countless seminars, webinars, and keynotes at industry-leading conferences. He assists clients worldwide with designing new data architectures. In 2018 he was selected the sixth most influential BI analyst worldwide by onalytica.com.
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DB Regio Bus, a subsidiary of Deutsche Bahn, has been executing a data strategy to support digitization and automation in a very decentralized organization. In this presentation, Asha, Marcus, and Christian will provide insights, methods, and lessons learned about the data strategy at DB Regio Bus and their experiences related to its successful execution.
Target Audience: Chief Data Officers, Chief Digital Officers, Data Manager, Data Governance Manager, Data Governance Directors
Prerequisites: None
Level: Basic
Asha Joseph Pattani is responsible for Enterprise Architecture and Digitalization at DB Regio Bus. She has vast experience in data management, digitization, and software architecture for large-scale systems. In her previous positions, she has experience in diverse industries and domains where Data was harnessed to drive digitalization. Asha established and is responsible for the data platform and its integrations into enterprise systems. From a technological and architectural perspective, she emphasizes the importance of data excellence, automation, and modular architecture. The introduction of digital assistants was one of her digitalization initiatives.
Marcus is Head of ICT at DB Regio Bus. He has a long experience in data management, digitization and public transportation. After previous positions in transport management, e-commerce and M&A, he took over the position as Head of ICT in 2014 with the ambition to modernize the ICT of the bus company of Deutsche Bahn. Marcus established a 100% cloud strategy and renewed the whole IT-infrastructure for around 9.000 employees. At present, the focus of his team is digitization, automation and modularization. In this context, Marcus successfully established the data excellence initiative of DB Regio Bus.
Dr. Christian Fürber is founder and CEO of the Information Quality Institute GmbH (iqinstitute.de), a specialized consultancy for Data Excellence and Data Management solutions. Prior to founding IQI in 2012, he held several data management positions at the German Armed Forces where he designed and executed the Forces’ Data Management Strategy. Since his leave from the Forces, Christian and his team have successfully established data management framworks for many companies in Europe helping them to accellerate innovation and digitization through data. Christian is also author, lecturer and speaker and organizes the TDWI Themenzirkel "Data Strategy & Data Governance".
Dr. Christian Fürber is founder and CEO of the Information Quality Institute GmbH (iqinstitute.de), a specialized consultancy for Data Excellence and Data Management solutions. Prior to founding IQI in 2012, he held several data management positions at the German Armed Forces where he designed and executed the Forces’ Data Management Strategy. Since his leave from the Forces, Christian and his team have successfully established data management framworks for many companies in Europe helping them to accellerate innovation and digitization through data. Christian is also author, lecturer and speaker and organizes the TDWI Themenzirkel "Data Strategy & Data Governance".
Michael Kolb ist seit 14 Jahren im Business Intelligence-Umfeld tätig - davon seit über 8 Jahren als BI-Projektleiter und BI-Architekt im BICC der HUK-COBURG. Seit zwei Jahren begleitet er die Themen Data Cataloging und Data Governance im Kontext des erweiterten Daten-Ökosystems der HUK-COBURG.
Dr. Sönke Iwersen verantwortet seit mehr 15 Jahren Data & Analytics-Organisationen in verschiedenen Industrien (u.a. Telefónica, Handelsblatt, XING, Fitness First, HRS). Schwerpunkte sind die Entwicklung von Digitalisierungs- und Datenstrategien und deren Operationalisierung mit cloudbasierten analytischen Plattformen und ML/AI-Lösungen. Er präsentiert seine innovativen Ergebnisse regelmäßig auf nationalen und internationalen Konferenzen.
Axel Schaefer ist der Global Lead Bilfinger Business Systems, umfassend verantwortlich für die bedarfsorientierte Pflege und Weiterentwicklung des Konzern-ERPs. Vertiefte Fachkenntnisse in Recht, Steuerberatung, Bilanzierung sowie operative Leitungserfahrungen in Konzerngesellschaften helfen ihm seit Jahren bei der Einführung und Prozessharmonisierung der Bilfinger ERP-Landschaft.
Marcus is Head of ICT at DB Regio Bus. He has a long experience in data management, digitization and public transportation. After previous positions in transport management, e-commerce and M&A, he took over the position as Head of ICT in 2014 with the ambition to modernize the ICT of the bus company of Deutsche Bahn. Marcus established a 100% cloud strategy and renewed the whole IT-infrastructure for around 9.000 employees. At present, the focus of his team is digitization, automation and modularization. In this context, Marcus successfully established the data excellence initiative of DB Regio Bus.
Brigitte Lutz ist Data Governance-Koordinatorin der Stadt Wien, leitet das Open Government-Kompetenzzentrum und ist Gründungsmitglied & Sprecherin der Cooperation Open Government Data Österreich. Weitere Aufgabenschwerpunkte sind der Digitale Zwilling der Stadt Wien, Data Analytics, Blockchain, E-Government-Bausteine und -Services. Sie hat eine postgraduale Ausbildung in Management & IT.
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Petrol is Slovenian company that operates in 8 countries in SEE with 5BEUR annual revenue. As traditional publicly-owned company, Petrol has faced necessity for transformation to stay ahead in highly competitive market. Use of BIA was mainly reactive, but in recent years it has transformed into competitive advantage by using cloud technologies and industry specific analytical models and focusing on the content and creating business value. This value is now being leveraged as competitive advantage through proactive use of data and analytics.
Target Audience: Decision Makers, Data Architects, Project Managers
Prerequisites: None
Level: Basic
Extended Abstract:
Petrol is Slovenian company that operates in 8 countries in SEE with 5BEUR annual revenue. Main business activity is trading in oil derivatives, gas and other energy products in which Petrol generates more than 80 percent of all sales revenue and it also has a leading market share in the Slovenian market. Petrol also trades with consumer goods and services, with which it generates just under 20 percent of the revenue. Use of BIA was mainly reactive, but in recent years it has transformed into competitive advantage by using cloud technologies and industry specific analytical models and focusing on the content and creating business value. This value is now being leveraged as competitive advantage through proactive use of data and analytics. Presentation will cover main business challenges, explain technology architecture and approach and discuss results after three years of system development and use.
Andreja Stirn is Business Intelligence Director with more than 20 years of experience working in the Oil & Energy and Telco industry. Skilled in Data Warehousing, Business Intelligence, Corporate Performance Management, Market Research and People Management.
Dražen Orešcanin is Solution Architect in variety of DWH, BI and Big Data Analytics applications, with more than 25 years of experience in projects in largest companies in Europe, US and Middle East. Main architect of PI industry standard DWH models. Advised Companies include operators from DTAG, A1 Group, Telenor Group, Ooredoo Group, Liberty Global, United Group, Elisa Finland, STC and many companies in other industries such as FMCG and utilities.
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Often, existing data architectures can no longer keep up with the current 'speed of business change'. As a result, many organizations have decided that it is time for a new, future-proof data architecture. However, this is easier said than done. In this session, ten essential guidelines for designing modern data architectures are discussed. These guidelines are based on hands-on experiences with designing and implementing many new data architectures.
Target Audience: Data architects, enterprise architects, solutions architects, IT architects, data warehouse designers, analysts, chief data officers, technology planners, IT consultants, IT strategists
Prerequisites: General knowledge of databases, data warehousing and BI
Level: Advanced
Extended Abstract:
Many IT systems are more than twenty years old and have undergone numerous changes over time. Unfortunately, they can no longer cope with the ever-increasing growth in data usage in terms of scalability and speed. In addition, they have become inflexible, which means that implementing new reports and performing analyses has become very time-consuming. In short, the data architecture can no longer keep up with the current 'speed of business change'. As a result, many organizations have decided that it is time for a new, future-proof data architecture. However, this is easier said than done. After all, you don't design a new data architecture every day. In this session, ten essential guidelines for designing modern data architectures are discussed. These guidelines are based on hands-on experiences with designing and implementing many new data architectures.
Which new technologies are currently available that can simplify data architectures?
What is the influence on the architecture of e.g. Hadoop, NoSQL, big data, data warehouse automation, and data streaming?
Which new architecture principles should be applied nowadays?
How do we deal with the increasingly paralyzing rules for data storage and analysis?
What is the influence of cloud platforms?
Rick van der Lans is a highly-respected independent analyst, consultant, author, and internationally acclaimed lecturer specializing in data architectures, data warehousing, business intelligence, big data, and database technology. He has presented countless seminars, webinars, and keynotes at industry-leading conferences. He assists clients worldwide with designing new data architectures. In 2018 he was selected the sixth most influential BI analyst worldwide by onalytica.com.
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