Category - Data Innovation Summit 2018

In this session you will learn about how you can accelerate your models into production. Imagine that you can cut the regular 6-12 months of development time into weeks, minutes. Questions: How can you leverage best...

When IBM’s Artificial Intelligence technology beat the most successful Jeopardy! Champions back in 2011, it made not only headline news and IBM Watson a household name, but it also ushered in what IBM has defined...

In today’s data driven world it’s extremely important to make sure that our data infrastructure is fast, efficient and quickly adapts to the changing business needs. At Uber, we use machine learning and artificial...

Having a dynamic enterprise system looks to many organizations as a far-fetched target. Owing to the vast amounts of factors that need to be controlled across the implementation lifecycle; especially during usage and...

Traditional segmentation strategies rely on clustering based on aggregated characteristics. One of the risks of this approach is that the difference between segments can be minimal and not very descriptive: by...

There is not the perfect RPA tool. It depends on the process to be automated. There are processes, which are easier to automate compared to other processes. How Merck Business Services implements RPA. Questions: How to...

Deep Learning has been delivering state of the art results across a growing number of problems and domains. Correspondingly, Deep Learning models are being deployed across a growing number of applications and use cases...

There are many challenges with getting started with deep learning and the latest AI techniques, especially in industrial settings with noisy data, immature tooling, and lacking supporting infrastructure. However, the...

The race is on for GDPR compliance, and now it is time to get hands-on with personal data. Recent surveys highlight that the toughest operational challenges for compliance are related to Data Management. This session...