23 - 24 October, 2019
Hotel Palace, Berlin
+44 (0) 207 368 9850
Day 1 - Wednesday 23rd October 2019
Wednesday, October 23rd, 2019
8:45 AM Chairperson’s Opening Remarks
9:35 AM Panel Discussion - Overcoming black box analytics: How can you build explainable AI in-house to increase trust with transparent data models and secure board backing to further automate the enterprise?
- How can you ensure that your Advanced Analytics / AI models are solving the business problems you need solved?
- Ensuring ethical AI: What is the best approach to integrating a strong code of data practice across the enterprise to ensure ethical and proficient advanced analytics?
- Building a reliable ethics framework: What are the technical tools and techniques required to address the privacy and security concerns surrounding increased automation to ensure responsible AI applications?
- Building a code of ethics: How to equip your data teams with ethical guidelines to counteract inherent bias in algorithm development and build fair data models that enable unbiased business decision making
- Setting governance standards: How can we increase collaboration across the data science community to build an official ethics framework to ensure responsible design and application of AI?
10:35 AM Fire Side Chat - How to find a north star metric to guide your organisation and stay ahead of the curve in rapidly evolving markets
- How can data help you connect strategy to execution? And how do you you best position analytics as a board level priority to empower the organisation with actionable insights that inform future commercial strategies?
- Creating a hypothesis driven business: How can you enable experimentation at scale with company data to identify new opportunities and fuel company growth?
- Succeeding with data storytelling: How can you make data part of day to day conversation in order to succeed in building a data-rich business culture?
11:45 AM 360 Panel Discussion - Succeeding with rapid experimentation and deployment: What are the critical success factors in organising your people, processes and technologies to successfully implement agile workflows across the business?
- How can you build flexible data strategies that evolve in line with new technologies and organizational processes to best support business decision making?
- Succeeding with data-agility: How can you break down big data with agile processes and enable your analytics team to better handle increasing volumes of company data?
- How can you introduce agile workflows across the data department to continuously deliver on data projects that reinforce data’s value to the business?
- How to create a blueprint for agile analytics to break down internal silos and fully operationalise analytics across the business