Day 1 - 19 June 2019
Justin van der Lande
Principal Analyst, Research
09:40AM - Day 1
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 2018, 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.
Case Study: Wonderware
Discussing new use cases for the data produced by IoT hardware, from video analytics to customer product usage data that can aid marketing.
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
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
To follow soon…
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.