Day 1 - 19 June 2019
Data Analytics for AI and IoT: Chair’s welcome and opening remarks
CDO / IT Head / Chief of Staff
10:00AM - Day 1
Bringing Offense and Defense together – Shoppable Data For Data Based Services in Analytics & ML
- Problem: 80% prep time for data analytics
- Root cause: Quality, sourcing, relevance of data
- Path forward: Bring DG to good data definitions, provide info architecture and drive modelling
- Use case: Framework to make data shoppable
Dr. Mohamed Anas
10:30AM - Day 1
Keynote: Analytics and AI Strategies for IoT, Catalyzed by Simulation
The buzz about Internet of Things (IoT), Analytics, and Artificial Intelligence (AI) is deafening. Predictions abound that these will power a massive shift in the roles that computers play in our personal and professional lives: enabling automated driving functionality, predicting maintenance of industrial equipment, delivering intelligent home health care systems and robots, and more. But, to get there, teams must combine specialized knowledge, domain expertise, and business objectives while navigating through numerous choices – security, communication, data acquisition and preparation, algorithms, processors, architectural allocation, and more. Simulation can help them to keep their eye on the application, enable reuse while exploring trade-offs, and create the game-changing value for their organization. In this keynote, Mohamed Anas looks at the exciting opportunities and practical challenges of building AI into our systems and services, from prototyping to production while targeting edge nodes to cloud, using simulation as an enabler.
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.
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
Data Scientist and Blockchain Developer
12:40PM - Day 1
Smart Machine Bidding: An incentive solution for automated data transmission settlement in IoT networks
LPWAN (Low Power Wide Area Network) technology can be used together with blockchains as an infrastructure for IoT. This combination automates machine to machine transactions and provides a device data economy (e.g. in MXProtocol). Smart Machine Bidding (SMB), provides an incentive solution to automate the payments related to the flow of IoT devices data. By SMB, each gateway can offer different bids on its data transmission cost. The LPWAN devices can smartly choose a gateway to transmit their data with. Data driven algorithms are also used in the SMB to automate and optimize the procedure.
In general, the SMB helps to provide a cost effective shared LPWAN which both gateway owners and device owners can profit from. In this talk, SMB procedure, its applications, and corresponding data driven algorithms will be discussed.
Case Study: A3 Cube
To follow soon .…
Afternoon Keynote: AI, Big Data and Autonomous Vehicles
Business developer Advanced Analytics
Nederlandse Spoorwegen (Dutch Railways)
02:50PM - Day 1
Senior Data Scientist
Air New Zealand
02:50PM - Day 1
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.
CTO | CDO
04:30PM - Day 1
Building a Data Driven Culture, Master your Data Journey!
In this talk I will cover a pressing issue facing many companies today: the ever-present threat of disruption by more agile, insightful and empathetic newcomers. Fighting back requires adopting a data-led culture. Such must begin at home – with your team, your people.