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Day 1

Registration and breakfast

Introduction from Chair

Real time data analysis and ML

- Understanding time series forecasting
- Machine learning models for time series forecasting
- How to implement the models using open source libraries

Subha Tatavarti Head of Product and Strategy PayPal

Machine learning & AI best practice for forecasting

- Understanding time series forecasting
- Machine learning models for time series forecasting
- How to implement the models using open source libraries

Ilkay Altintas Chief Data Science Officer San Diego Supercomputer Center

Monetising your data

- Capturing your decision architecture
- Developing your monetisation strategy
- Sourcing, organising and stitching together data to build your solution

Mario Vinasco Marketing Analytics Manager Uber

Morning Coffee

Discussion table session

Choose a 30-minute discussion from across all three streams and learn from the experience of the discussion leader, your fellow delegates, and share your own perspective. Each discussion group is limited to seven participants.

Discussion table session

Choose a 30-minute discussion from across all three streams and learn from the experience of the discussion leader, your fellow delegates, and share your own perspective. Each discussion group is limited to seven participants.

Becoming a data-driven business

- Building and redefining your data strategy
- Creating the cultural change and removing barriers
- Adopting new technology

Samith Gunasekara Head of Machine Learning and AI Analytics Boeing

Lunch

Holistic view of your customers using predictive analytics

- Customer insights
- Location market insights

Zheng Shao Analytics and Strategy Data Scientist Facebook

Discussion table session

Choose a 30-minute discussion from across all three streams and learn from the experience of the discussion leader, your fellow delegates, and share your own perspective. Each discussion group is limited to seven participants.

Discussion table session

Choose a 30-minute discussion from across all three streams and learn from the experience of the discussion leader, your fellow delegates, and share your own perspective. Each discussion group is limited to seven participants.

Panel: Creating a data driven culture

- How does audience analytics solve the disconnect
- Focusing on consumer actions
- Sharing data across departments

Scenario planning Workshop – Data breaches

- We will be presenting you with a series of data breaches case studies. Your task with your team will be to come up with an in depth plan of your next steps at each stage.
- How could this have been prevented?
- Steps to ensure this doesn’t happen again?

Closing remarks from Chair - Drinks

Day 2

Registration and breakfast

Introduction from Chair

Application of predictive analytics in Healthcare

- Predicting risk scores for healthcare insurers
- Preventing hospital readmissions
- Clinical variation management

Transform the freight rail industry. Innovations in the industry

- Innovations in the industry
- Dealing with large amounts of data
- Understanding the advanced database platform

Fred Ehlers CIO Norfolk Southern Corporation

innovation in Infrastructure: How the Smart City Really Thrives

There’s been plenty of discussion around sensors and data management in the smart city – but what about the core of all urban environments, infrastructure? We discuss how investments in infrastructure – and often the infrastructure we can’t see – positively impact smart city initiatives and make a substantial difference in the day-to-day lives of citizens.

Adam Tank Director of Smart Cities Suez

Morning Coffee

Workshop - The Best and the Worst of Predictive Analytics: Predictive Modelling Methods and Common Data Mining Mistakes

- How do you pick the right one to deliver the greatest impact for your business, as applied over your data?
- What are the best practices along the way?
- How do you avoid the most treacherous pitfalls?

Lunch

Autonomous Data Warehouse Cloud – Self-sufficient database without human interaction

- How much storage do we need?
- New understanding of self-service
- Understanding the advanced database platform

Creating a predictive model using Deep Learning – Encouraging your business to find the commercial value.

- The dynamic nature of deep learning methods
- Creating greater personalisation of customer analytics
- Improving accuracy and performance in applications

Panel: Data analytics being the driver of your organisation

- Starting with why this is necessary
- Overcoming being overwhelmed with data
- Developing vision and strategy

Closing remarks from Chair - Coffee