CDAO Germany schedule

In the highly competitive age of digital transformation financial service organizations are facing accelerated urgency to improve their customer and employee experience while simultaneously reducing operating costs, and managing risk and compliance.

To meet these competing demands on their business, these organizations are racing to deploy deep learning to achieve a new competitive edge by optimizing their back office operations with intelligent document processing, personalizing their customer experience with cutting edge NLP models, and reducing fraud and risk using state-of-the-art deep learning.

AI is here and delivering new capabilities to help businesses solve large and complicated challenges. Join Bob Gaines to learn what that means for your business and how deep learning is helping organizations:

• Achieve higher compliance, faster and with lower costs • Dramatically improve Customer Experience • Reduce time to value from years to weeks

Sergio Rego is a customer engineer at SambaNova Systems where he helps clients deploy purpose-built, deep learning solutions in weeks rather than years. Sergio started his career in financial services, where he worked in strategy; active and index management; and product design and management. Sergio also served as a senior data scientist and team manager for a system integrator where he helped federal government agencies deploy ML and AI solutions.

• The momentum of trustworthy data.
• Transforming SAP into a data-driven enterprise with a strong data management and technology foundation.
• Creating a connected data architecture to support business agility and value.
• How we can infuse intelligence into business processes with AI.​

Achieving Value at Scale by Implementing AI & Advanced Analytics Across Different Levels of Maturity  

• What is the base data maturity level required for AI powered advanced analytics?
• How can this contribute to value creation in the business?
• Achieve a single, unified view of your customer data at speed with Artificial Intelligence
• Can AI solve the problem of being scalable when dealing with increasing data volumes?
• What is the value of automation & ML-Ops as part of this process?

Moderator: Sebastian Kaus, Data Governance Lead, Vattenfall

Panelists: 

• Cornelia Schaurecker, Global Group Director AI & Big Data, Vodafone
• Eswar Nagireddy, Senior Product Manager – Data Science, Machine Learning and Advanced Analytics, Exasol
• Pilar Moguel Macias, Product Analyst, Adidas Runtastic

• Maximize returns from data science investments
• Transition from analytics automation to enterprise transformation
• Drive and embed a data-led innovation culture

• How will the elements of a data science organization change?
• What kind of people do we need in the future?
• What are my lessons learned from other regulations having impacted the insurance industry?

Extracting business data from SAP applications for integration into a cloud-based architecture like a data lake or a data warehouse can be a huge challenge.

In this session Richard Brouwer, a worldwide leading expert on SAP data integration will share his best practices on:

• How to use log-based CDC as the most efficient way to extract your SAP data
• How to extract and enrich your SAP data for downstream pipelines
• What a scalable architecture to unlock your SAP data could look like

• What can be done to increase synergy with technology to overcome data silos?
• In a digital, and often hybrid/virtual working environment, what can you do to drive collaboration and innovation?
• How to navigate economic challenges with leadership strategy for digital transformation that drives growth
  
  Dmitry Kharchenko, CTO & CDO, Friendsurance

• Is a data driven culture achievable without executive leadership that doesn’t own and drive the usage of data?
• How much training do data champions need to break down silos and promote a culture of collaboration?
• Is a data driven culture even a concern until trusted data is sharable and accessible?
• How much is a data literacy a critical skill for every role?

Facilitators include:

• Sophia Beard, Head of Data and Analytics, Sanity Group
• Andrew Spires, EMEA Data Integrity Lead, Tricentis
• Rohit Vattipalli, Senior Manager - Data Engineering. Governance & Analytics, EIT Health

• How important is the ability to transcend traditional organisation barriers for a data executive?
• Do you need technical expertise to be a strong data leader?
• What are the major technological trends that require more devoted focus?
• Can someone without technical precision see through the hype and deliver a united vision for the whole organisation?

Facilitators include:

• Felix Kraemer, Head of Data & Analytics, H-Hotels.com
  
  

• Utilising AI to facilitate the energy transition 
• What role will quantum computing play in future transformations
• How drones have been harnessed to implement high voltage cables
  
  

•    What are the different ways data monetisation can be leveraged for a business?  
•    How to avoid missing and start seizing opportunities for data monetisation  
•    Navigating the regulatory challenges of data monetisation  
•    Creating a mind-shift with data as a quantifiable and tangible asset  

• What metrics can be used to measure data attributes?
• Creating a standardised product to be consumed by everyone
• Is data a product in itself or does it need to be tied to a predictive analytics model or automation

Moderated by: Lígia Rütgers, Head of Digital Field Technologies and Data Analytics, KWS Group

Panelists:

• Pedro Duarte, Head of Client Data Insights, BNY Mellon
• Fahim Alefi, Senior Vice President Data Strategy, ProSieben Sat.1 Media SE
• Dominik Müller, Head of Advanced Analytics- AGCS, Allianz
• Wim Stoop, Senior Director, Hybrid Data Platform, Cloudera

In this session, you will discover the key learnings from E.ON’s data transformation journey, to help you navigate through the different levels of maturity as well as how to lead and manage changes along the road.

•    When dealing with vast amounts of data, generate a framework for prioritising what data to bring under governance  
•    How to build appropriate controls for data governance to mitigate risk  
•    Establish key compliance benchmarks to continuously monitor and improve master data  
•    Ensuring data architecture includes standardisation and metadata management  

Panellists:

• Jochen Grömping, Director Global Data & Analytics, ALDI SÜD 
• Daljeet Singh, Data Governance Program Lead, Siemens Healthineers 
• Evgeni Hasin, Director of Analytics, Wefox
• Poonam Mishra, Senior Manager, Data Governance, Sky Media