- How the business intelligence problem facing executives today is impacting decision-making
- Making fast decisions underpinned by AI-powered dashboards that interpret the data and generate insights
- What is the best practice industry uses cases for automated insights using natural language generation and expectations of time, investment and value
- What is Explainable AI? And, what is currently lacking in the AI/ML/Analytics?
- What are the driving forces of XAI?
- Understanding the Impacts of explanability and interpretability in industry; including autonomous vehicles, healthcare and finance
- Balancing trust and AI-enabled systems; How can and should we trust AI-enabled systems?
- How do data-driven leaders approach business differently?
- Leadership that empowers the analytics team
- Key traits of analytics professionals that impresses the c-suite
Moderated by Stephen Porges
- Understanding the impact of AI on healthcare transformation
- Solving real-world problems using purpose built AI solutions
- Life Whisperer – a case study of successful application of AI to improve pregnancy outcomes for patients undergoing IVF
Data warehousing is dead, long live data warehousing!
At an increasing rate, organisations across many industries are creating and applying innovative data-analytics driven applications for everything from improving internal, operational processes and to providing exceptional customer experiences. All depend on timely and reliable analytics.
This session explores new world, built-for-the-cloud architecture and gets under the hood of the technology that combines diverse data sets, automatically scales to meet ever changing application demands while delivering consistently great performance.
- Preparing your organisation for a future at the speed of light
- Harnessing exponential technologies like IoT and big data
- Do we all need robotics, analytics and blockchain in business?
This session focuses on how to add artificial intelligence into your analytics analysis - from the collection of streaming data and preparation of structured and unstructured data through to the analysis using machine learning and AI. This tutorial will walk you through the IBM micro-service information delivery concepts and how you can add Watson-based services to your next initiative. Join Kieran as he goes under the hood of next generation business insights, data integration and AI-enabled analytics.
- The business implications of mass data collection
- How analytics leverages even the most innocuous dataset
- Is there hidden revenue streams in your data and analytics?
- Approaches to aligning business strategy and analytics capability
- Delivering win-win outcomes to analytics teams and business stakeholders
- Team development as an objective not an after thought
Machine learning / artificial intelligence are noted as the most highly sought skills in recent IAPA surveys. With various programs and options available to build machine learning models, analytics professionals are also faced with increasing time pressures to build, train and deliver to production machine learning models. Join Data Scientist John Hawkins for this deep dive into the automated AI platform used by Virgin Australia and medical insurer Avant. The indepth session will demonstrate how the platform from DataRobot can train and validate various ML models rapidly - with the chosen model able to easily scale to production environments.
- Juggling expectations of internal stakeholders, patients, clinicians and the analytics team
- Why both a top-down and bottom-up approach matters for success
- Digital transformation lessons from a healthcare setting
Deep neural networks are complex and opaque. As they are used in a variety of important and safety critical domains, ways to explain predictions are being sought. Join Brian in this deep dive session that technically explains explainable AI.
Brian will share an approach to explaining deep neural networks by constructing causal models on salient concepts using autoencoders trained to extract human-understandable representations of network activations. This results in the ability to identify and visualize features with significant causal influence on final classification.
- How might business stakeholders and customers interface with analytics
- Will analytics & AI be the new face of an organisation
- What skills are going to be required to enable this direction?
A sneak peek at the outcomes of the 2018 IAPA Skills and Salary Survey
- Which skills are in demand?
- Has the median salary changed?
- How difficult is hiring analytics professionals?
- When the rubber hits the road, what can your analytics really reveal?
- How to know if AI / ML is right for your business and understand the implications
- Bringing the analytics team on the advanced analytics journey too
- Improving the world with analytics
- Recognising and reducing algorithmic bias for better outcomes
- Using machine learning to solve large-scale problems