Keynote Panel: Succeeding in the Cognitive Age – Exploiting the Potential of Artificial Intelligence & Beyond
• What does a ‘Cognitive Enterprise’ look like in the real world, and what are the steps to becoming one? • How mature are Artificial Intelligence solutions currently, what can they achieve within the business context, and what should we prepare for in the coming years? • Where to begin – Approaches to acquiring the… Read more.Speaking
Discussion Group Session 1
• Beyond Volume, Variety, Velocity, and Veracity – Reaching the ‘Fifth V’; Value • Data as a source of innovation – utilizing your information to out-compete your rivals • How can we move the data function from a perceived cost center to a respected profit center?
• What steps can we take to best enable disruptive innovation through the use of Machine Learning? • How do you collate and prepare datasets to maximize success of machine learning algorithms? • Will the rise of machine learning lead to a decreased demand for Data Scientists as they are replaced by self-learning algorithms?
• Delivering insights to wow the customer and improve retention & profitability • Using customer data and cognitive systems to deliver true personalization • Avoiding the ‘creepy factor’ – how far are the public ready for us to go?
• Exploring eco-systems – building an effective environment for your enterprise’s data • Ensuring that your infrastructure is ready for the future – preparing for AI workloads and more • Using cognitive solutions to accelerate your architecture – automating roles, policies, and consent
Discussion Group Session 2
• Immediate impact – what are the common ‘low hanging fruit’ and where should we turn once these have been utilized? • Proving strong return on investment to earn trust and demonstrate value. • Avoiding becoming a ‘flash in the pan’ – how can we ensure a long term, continued willingness to invest in data?
• Exploring the benefits and limitations of utilizing Cloud infrastructure • Private, Public or Hybrid – which route suits which circumstance? • Have security concerns been sufficiently addressed within Cloud technologies for them to be developed in an enterprise setting?
• Building trust – How can we become vital partners, rather than rivals, for the Marketing function? • Measuring ROI – providing data and developing metrics • Using predictive analytics to estimate churn and improve planning
• Establishing a strong governance framework to ensure high quality, consistent, and actionable data • Embedding a culture of responsibility amongst all data users so that governance remains a priority in coming years • Future proofing – what steps can we take now, to maximize the likelihood that today’s procedures will be ready for tomorrows… Read more.
Discussion Group Session 3
• How should potential projects be identified and prioritized? • Earning the trust of potential internal customers in lines of business • Communicating how the data & analytics function can aid value, without over-promising and under-delivering
• What opportunities does Blockchain present, and how can we ensure we are best placed to exploit them? • How might we need to adjust our data governance and management practices to order to accommodate Blockchain usage? • Overcoming volatility and developing standards – When should we expect to see Blockchain in production use cases?
• Building a strong relationship with Product Development teams, based on mutual trust • Discovering gaps in the market through analytics and sparking creative solutions to them • Using data to refine and optimize existing products and services
• Eliminating inefficiencies through data – where can the big cost reductions often be found? • How can the application of analytics increase revenues across the whole business? • How can analytics improve assessments of financial performance, to optimize budgeting and forecasting?
Discussion Group Session 4
• How far can enterprises adopt a startup approach? • Which advantages are innate to startups, and which can larger enterprises replicate? • What methods can be used to increase collaboration between siloed departments within large organizations?
• How can your data program support wider transformation within your organization? • Should digital transformation be a cross functional responsibility, and what is the CDAOs place in this? • Positioning the CDO as a vital partner for success in digital
• Be the disruptor, not the disrupted! Utilizing data & analytics to devise novel business models • Testing and validating original revenue generating ideas through predictive modeling • What are the best examples of innovative business models created through analytics, and what can we learn from them?
• Do we need dedicated ‘data translator’ roles, or should we expect all team members to perform this duty? • Unlocking the secrets of communicating with non-data colleagues • What role can visualization play in communication our findings, what how can we ensure it is understood by all?
This session provides a deep dive into crucial areas for any data and analytics leader: Analytics, Storage, and Power. The session will provide all attendees with an essential briefing on the latest developments in each area, as well as provide actionable advice to supercharge your organization’s efforts. Speakers will provide an overview into each area,… Read more.Speaking
Keynote Panel: Data Science Versus Data Engineering – Striking the Right Skills Balance within your Team
• What is the difference between Data Engineers and Data Scientists, and what should they each be doing within your function? • Stop hunting for Unicorns that don’t exist! How to successfully split the workload between Engineers & Scientists and reap the rewards of utilizing complementary skills sets. • Don’t feed your models garbage –… Read more.Speaking