Day 1 - 19 June 2019
Data Analytics for AI and IoT: Chair’s welcome and opening remarks
Edge processing for data analytics and training AI Algorithms
- How the huge influx of data will require fit-for-purpose architecture. What is the distance from the edge to your device and how to consider this during the creation of your IOT / AI architecture?
- Discussing how IoT / AI architectures need to be put in place to ensure increased compatibility across domains.
- Using cloud analytics platforms to derive value from IoT / AI data vs physical gateways -pros and cons.
Keynote: Information is everything
Data is the new oil is a familiar paradigm in 2019, but until we learn to process and derive actionable insights from this data how valuable is it? This talk will cover a real life case study where a business has successfully taken data generated by the IoT and converted into into real business actions. Hear about their journey, and their recommendations for uncovering new economic structures made available by access to intelligent data.
Consultant Manufacturing Analytics
11:30AM - Day 1
How to start with Big Data Analytics in Manufacturing?
Due to the exponential growth of process data in production facilities, manufacturers are facing data challenges they didn’t face a few years ago. Nowadays a factory (shop) floor produces even more data than it produces products. Batch data, machine data, operational data, energy data and sensor data: all examples of valuable data that is captured in a factory. In this presentation you will learn how industrial data differs from traditional marketing & sales data, what the major challenges are and how Wonderware Benelux have helped several key players in the industry to take the first steps in analysing big data from the factory floor.
Dr. Maher Chebbo
Senior Executive SVP, Chief Business Innovation Officer
02:00PM - Day 1
12:00PM - Day 1
Panel: IoT and AI data analytics for intelligent decision making
- Identifying target-rich, high-value data that can be used to generate business intelligence
- Using cloud analytics platforms to derive value from IoT data
- Discussing the barriers to widespread IoT/ AI /Big Data value delivery and how these might be overcome.
- Real time data analytics in practice – examples of how IoT / AI data is creating business efficiency and revolutionising working practices
Principle Product Manager
12:40PM - Day 1
Building High performance and Highly available Hadoop cluster. Practical lessons
Key Aspects to a well configured Hadoop clusters.
It include 5 pillars:
- YARN performance tuning
- Spark performance tuning
- Set up Static Service pools
- Set up Dynamic Service pools
- Setup Hadoop cluster in Highly available way
Case Study: A3 Cube
To follow soon .…
Afternoon Keynote: AI, Big Data and Autonomous Vehicles
Panel: Big Data – Creating Intelligent Data Models
- The increased need for big data analytics to drive AI & Machine learning
- How to successfully unlock unstructured data & transform into learnable features
- The advancement of self-service big data tools & its benefit for your organisation
Senior Data Scientist
03:30PM - Day 1
This talk will be given by Kia Eisinga, Senior Data Scientist at TomTom
Institute for Ethical AI & Machine Learning
04:00PM - Day 1
Industry-ready data & machine learning pipelines
This talk will provide a practical deep dive on how to build industry-ready machine learning and data pipelines in Python. I will cover a hands-on case study that will build from the basics of Airflow, and show how it is possible to build scalable and distributed machine learning data pipelines using a distributed architecture with a producer- consumer backend using Celery. I will provide insights on some of the key learnings I have obtained throughout my career building machine learning systems, as well as caveats and best practices deploying scalable data pipelines systems in production environments.