CDAO Perth schedule

During this 10-minute networking session, the aim of the game is to go and meet three people you don't already know. Have fun!

• Leveraging drone imagery, satellite data, and 200+ live weather stations to create unified data ecosystems.
• Challenges in aggregating fragmented environmental and agricultural datasets.
• The role of open data in enabling collaboration and accessibility (government-led initiatives.

• Lessons learned from implementing domain-oriented data ownership, product thinking, and federated governance across complex, distributed environments.
• How to empower individual teams while maintaining interoperability, quality, and security across the enterprise.
• What comes next—how emerging architectures (e.g. data fabric, AI-native platforms) and business needs are reshaping the future of distributed data innovation 

Despite growing investment in AI and analytics, many organisations still struggle with fragmented data ownership, inconsistent quality, and siloed systems that limit business impact. This session explores how data leaders can build trusted, scalable foundations that enable smarter decisions, stronger governance, and enterprise-wide AI readiness.

• Establish clear data ownership and enterprise-wide governance to create trusted, accountable data foundations.
• Improve data quality and interoperability across agencies, systems, and business functions.
• Build organisation-wide data literacy and stewardship to drive adoption and lasting cultural change.
• Scale self-service analytics and AI readiness with accessible, governed, and trusted data platforms.

Speakers:

Ivy Isaac
Manager - Governance, Analysis and Improvement
Fortescue

Aqif Mukhtar
Manager - Data Analytics
Road Safety Commission

Vaibhav Agrawal

AI Technology Advancement Committee

Australian Computer Society (ACS)
 

• What changes are required in your current data architecture to support scalable and reliable AI workloads?
• How can metadata management and lineage tracking help build trust and transparency in AI-driven decisions.
• What governance and pipeline strategies ensure AI doesn’t amplify existing data quality or compliance issues.

Most organisations have moved beyond asking whether they should invest in AI. The challenge now is how to move from isolated experiments to AI that can reason, decide and act safely inside core business processes.
The barrier is no longer the model alone.

Fragmented systems, inconsistent data, missing business context, static governance and uncontrolled AI consumption all undermine trust, increase cost and prevent value at scale. In this session, Mitch Howard, Solution Engineer at Boomi, explores the infrastructure required to turn AI into governed action.

Drawing on new APAC research and real-world examples, he will examine how organisations can connect and activate trusted data, ground agents in business context, govern access and behaviour, and combine deterministic automation with agentic workflows to deliver measurable outcomes.

Attendees will learn why AI readiness is only the starting point—and how data, context, integration and control must work together to move AI from insight to enterprise action.

• Strengthen data maturity and trust by improving data quality, integrity, and cross-business transparency.
• Transform data teams into strategic business partners through better communication, stakeholder alignment, and operating models.
• Embed data into business decision-making by shifting from static reporting to actionable, insight-driven conversations.
• Expand platform value by integrating new data sources while aligning outputs to evolving business needs.

• Problem statement: Despite best efforts, true self-service remains elusive, hindered by governance bottlenecks, complex tooling, and lack of data literacy.
• What we’ll explore: The key considerations, challenges, and complexities that organizations face today.
• Key outcome: Forward looking strategies for democratizing data, empowering business teams to make confident, data driven decisions while reducing reliance on technical teams. 

Data leaders face constant pressure to move faster while avoiding costly missteps. Decisions to buy, build or partner shape not just delivery speed, but long‑term flexibility, risk and credibility. How do you make these calls in practice, separate substance from vendor noise, and structure partnerships that support evolving business needs?

Speakers:
Andy Maher
Manager – Digital & Data
IGO Ltd.

Nikhil Matthew
AI & Enablement Lead
Edith Cowan University

• Design access models that support agility.
• Balance privacy obligations with business demand.
• Automate controls through platforms and metadata.
• Reduce bottlenecks  caused by manual approvals. 
  

• Securing replication environments to prevent leakage, duplication risk, and shadow data.
• Building integration layers that preserve lineage, metadata, and access control across platforms.
• Safeguarding sensitive datasets in AI/ML workflows without limiting performance or agility.
• Aligning with governance frameworks to ensure ethical, compliant AI adoption from the start. 

• What strategies work best for modernising legacy systems without causing disruption to critical business operations?
• How do you prioritise which parts of the data stack to replace, refactor, or integrate with modern platforms?
• Make What role do cloud, APIs, and data virtualisation play in extending the value of legacy investments?

• Align data mesh architectures with robust governance to enable trusted, scalable data.
• Deliver enterprise agentic AI frameworks with embedded guardrails and controls.
• Balance innovation with risk through practical governance and ethical AI practices.
• Drive adoption by managing cost, change, and measurable business outcomes. 

• Identify where governance creates unnecessary friction.
• Redesign controls for modern data and AI use cases.
• Clarify ownership for risk and assurance decisions.
• Maintain trust while increasing pace.

• How can AI models be trained and tuned to identify subtle data quality issues and drift before they impact downstream use?
• What’s the right balance between automated detection and human oversight in managing data reliability?
• How do you integrate real-time monitoring into existing data pipelines without introducing latency or complexity?

• How can organisations move beyond policy on paper to embed governance into the tools, processes, and platforms teams already use?
• What are effective strategies for federating governance responsibilities without losing oversight or consistency?
• How can automation, metadata, and cataloguing tools support real-time, scalable governance practices across the enterprise?

Conventional wisdom says governance and speed pull in opposite directions. This session makes the opposite case: that proactive governance is one of the most powerful accelerators of AI innovation available to an organisation. We’ll explore how the right mindsets, scalable architectures, and practical guardrails work together to let teams experiment boldly and ship responsibly — at pace. Attendees will leave with a practical playbook for building data and AI capability that keeps up with fast-moving technology and market expectations, without trading away trust, control, or compliance.

Many Perth organisations have reached a practical hiring ceiling due to budget pressure and talent scarcity. The focus has shifted from adding people to changing how data teams operate and prioritise.

• Why does hiring top technical talent individually not guarantee
  a high-performing team?
• Evaluate where AI tools genuinely augment teams versus add complexity
• How do you foster collaboration and proactivity in newly formed data teams?
• What hiring and retention strategies help turn strong individuals into a cohesive
  unit that delivers value?

Speakers:
Douglas Robertson Director & Principal Consultant DR Analytics Recruitment

Speakers:

Sandhya Krishnan
GM, Organisational Solutions, People Tech & Analytics
RAC WA

Ross Campbell
Manager - Data Analytics & Privacy Officer
The Perth Mint

Get ready to challenge assumptions, defend your stance, and shift perspectives.
In this high-energy, interactive debate panel, senior data leaders won’t just share insights. With live audience polling and daring prompts, this session invites attendees to vote, question, and engage in real-time. Expect lively discussions, surprising consensus, and a candid look at the questions shaping the future of data leadership in WA.

• How can CDAOs scale AI responsibly while ensuring governance and compliance keep pace?
• What strategies build trust across the business, so AI adoption is embraced,
  not resisted?
• How do leaders balance the urgency for AI-driven growth with the risks of misalignment or misuse?

Speakers:

Matthew Curnow
Head of Digital Strategy, Data Management & AI
Wood

Harpreet Khalsa
Chief Data Officer
Edith Cowan University

Rod Pedero
Data & Analytics Manager – Strategy Enterprise Architecture & Data
Western Power

Krista Bell
Director – Data & Information Governance
Curtin University