AGENDA - DAY TWO

• Cloud Performance and Optimization in an energy trading setting
• Best practise in applying the tools and methodologies of DevOps to your cloud approach
• Cloud privacy and security ensuring compliance with GDPR and other regulations
• The real user cases: innovation in the cloud; what can we learn from outside of the energy trading sector?

Senior representative from innovation team, Microsoft

• Assessing whether the data lake is the right solution for your organisation: pros and cons
• Data discovery, selection, and provisioning
• Developing and optimising your data ingestion and dispersal framework
• From data lake to data science – An overview of the external tools available in your journey
• The role of machine learning in the data lake

Surya Ayyagari, Senior Data Manager, Uniper Global Commodities SE

In this session, NorthGravity, along with an energy trading firm will outline the steps they took and results seen through the implementation of the Northgravity  solution, covering:

• Data Pipeline (lake, preparation, storage) 
• Data science
• Model Management
• Serverless & Cloud
• Prescriptive insight 

Travis Nadelhoffer, CEO, NorthGravity

• What are the trends in the ETRM world?
  • Toward ecosystems rather than monolithic set-ups?
  • SaaS: Are the subscription-based systems the future?
  • What cloud-based means – Advantages and drawbacks analysis
  • Business drivers
  • Implementation: Does it have to be long and laborious?
  • Success stories
     

MODERATOR: Dr Gary Vasey, Partner & Managing Director, ComTech Advisory

Hugo Stappers, Director of Sales & Marketing EMEA, Pioneer Solutions
Roland Bäck, Head of ETRM & Trading Process Management, OMV

With so much focus on digitalisation in the front office, this session explores Centrica’s practical initiatives and successful digital implementations in the back and middle offices.

Rahul Malik, Head of Trading IT, Centrica 

• How should you redesign your operating models and business processes to maximise the use of technology and resources?
• Developing a holistic system to identify problems and threats to your automated trading systems
• Leveraging new technologies to improve post trade processing, clearing & settlement
• Implementing machine learning based models into live trading systems
• Managing, governing and integrating data to optimise performance across applications, systems and services

• What is the level of AI uptake in the energy trading sector? Of those firms with AI programs what have been the outcomes?
• Looking out of industry – AI success stories in finance and other sectors
• Moving from machine learning to AI in pricing and modelling
• Quantum machine learning and its future applicability to energy trading
• How should regulations and ethics in AI influence your strategy?
• Developing a culture to allow AI to thrive within the organisation

Kasper Walet, Founder, AIEnergizer
Aideen Cardiff, Watson AI and Industry Channel Leader UKI, IBM