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YOW! Data is a technical conference for data professionals which provides the opportunity to share challenges, best practices, experience, techniques and tools.

The conference brings together leading industry practitioners and applied researchers working on data-driven technology and applications, providing in-depth coverage of current and emerging technologies in the areas of Big Data, Analytics and Machine Learning. Network, meet the experts and hone your skills all in one event.

Keynotes and Invited Speakers

Lessons from Building a Data Platform for Smart Cities

  • Simon Kaplan
    [ui!] the urban institute

How to Experiment Quickly

  • Juliet Hougland
    Data Vagabond
    Bagged & Boosted


Practical Learning To Learn

  • Mat Kelcey
    Machine Learning Principal

Making The Black Box Transparent: Lessons in Opacity

  • Xuanyi Chew
    Chief Data Scientist

Sketch algorithms

  • Simon Belak
    Mad Scientist

Entity Resolution at Scale

  • Huon Wilson
    Sr. Software Engineer
    CSIRO's Data61

Emerging Best Practices for Machine Learning Engineering

  • Lex Toumbourou
    Sr. Consultant

Practical Geometric Deep Learning in Python

  • Pantelis Elinas
    Sr. Research Engineer

Is Agile Data Science a thing now?

  • Hercules Konstantopoulos
    Sr. Data Scientist

Auto feature engineering - Rapid feature harvesting using DFS and data engineering techniques

  • Ananth Gundabattula
    Sr. Architect
    Commonwealth Bank of Australia

Bootstrapping the Right Way

  • Yanir Seroussi
    Distinguished Data Scientist

Which Plane Woke Snowy the Cat?

  • Simon Aubury
    Data Engineer Architect

Scaling Analytics as your Company Grows

  • Itzik Feldman
    Product Manager for Data Engineering and Analytics

The Magic of Unsupervised Learning: Teaching an AI to Understand Our World

  • Agustinus Nalwan
    AI & Machine Learning Technical Development Manager

From Zero to Tensorflow: Building an Analytics Dept.

  • Antoine Desmet
    Analytics Manager

My 5 Biggest Database Blunders

  • Brad Urani
    Staff Engineer

Search at Scale: Using Machine Learning to Automate Content Metadata

  • Gareth Seneque
    Machine Learning Engineer
    Australian Broadcasting Corporation

New Technologies to the Rescue of Epileptics

  • Robin Champseix
    Data Scientist
    OCTO Technology

Predictive Modelling for Online Advertising

  • Diana Mozo-Anderson
    Marketing Science Lead

Look at GDPR from a Data Engineering Perspective

  • Daniel Deng
    Sr. Data Engineer

Working with Large Numbers of Non-Trivial ETL Pipelines

  • Jessica Flanagan
    Chief Data Architect
    Deckard Technologies

The Sceptical Data Scientist

  • Linda McIver
    Executive Director
    Australian Data Science Education Instute

Transparent Government: The Stories we can Tell with Data

  • Mel Flanagan
    Content & Service Designer
    Nook Studios

Data Driven Diversity

  • Larene Le Gassick
    Inclusion Engineer

Modern Time-Series Methods

  • Kale Temple
    Co-founder & Practice Director
    University Of Sydney

From Sparse Data-sets to Graphs: When Explicit Relationships Bridge the Gaps

  • Enrique Bustamante
    Loyalty Data Analyst
    EB Games Australia

Bringing Continuous Delivery to Big Data Applications

  • Reza Yousefzadeh
    Principal Data Engineer

Game Engines and Machine Learning: Training a Self-Driving Car Without a Car?

  • Paris Buttfield-Addison
    Secret Lab
  • Mars Geldard
    University of Tasmania

Building a Scalable Data Science Pipeline at REA

  • Justin Hamman
    Sr. Developer
    REA Group
  • Jack Low
    Sr. Developer
    REA Group

Engineering an Ethical AI System

  • Simon T. O'Callaghan
    Sr. Research Engineer
    Data61 & Gradient Institute
  • Alistair Reid
    Sr. Research Engineer
    Gradient Institute
  • Finn Lattimore
    Research Scientist
    Gradient Institute
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