Saltar al contenido

Detalles

# Sydney All Things Data Meetup 2025 — 1st May at Microsoft Reactor

Biggest Event Yet! Please UN-RSVP if you cannot make it!! :-)

This is NOT a social group; it is a Data-Related Networking Event. Please note that if you are found or known to turn up for free food, you will be asked to leave and be banned.

📅 Thursday, 1st May 2025 | 🕔 5:00pm for 5:45pm start
📍 Microsoft Reactor, Sydney
Join us for the Sydney All Things Data Meetup — back bigger and better for 2025!
We're bringing together C-Level executives, Data Leaders, AI Specialists, and Platform Innovators to explore how data-driven platforms are transforming business success.
Expect real-world insights, live innovation challenges, and powerful networking with Australia's top data minds.

***

### 🔍 What to Expect

🎤 Expert Panel: “Innovating with AI – Balancing Vision and Practicality”
Our panel of renowned speakers will explore the complexities of building data and AI solutions that scale. You’ll vote in real-time on the most relevant subtopics, with panellists tackling your biggest questions live on stage.

✅ Confirmed Speakers:

  • Brett Wilson – CIO50 2024, 2023, 2022, 2021, 2020 & 2019 | Chief Information Officer | Digital Transformation | Royal Australasian College of Physicians, Australian Red Cross
  • Simon Aubury – Principal Data Architect, Qantas | Thoughtworks | Confluent Community Catalyst & International Speaker
  • Mimi Chattopadhyay – Co-founder of Tasnix, CDAO, CTO, Program Leader in Gov, Health, and Finance. NSW Rural Fire Service | NSW Treasury | News Corp
  • Fergal Cott - Director of AI Journey Labs, Data/AI at Brennan IT, Head of Data at Taysols and NRMA

⚡ Live Voting – You Decide the Questions
We’ll propose four headline data topics in advance, each with 3–5 sub-questions. Attendees vote live on what matters most, so the discussion is relevant, real, and responsive to your world!

💡 Innovation Challenge
Got a two-minute pitch or problem worth exploring? Step up and share it with the room.

🍷 Networking Mixer
From 5 pm, and after the panel, enjoy drinks, snacks, and open conversations with fellow data leaders and innovators.

***

### 🌐 Platforms & Topics in Focus

  • Multi-cloud strategies: Microsoft Fabric, Azure, AWS, GCP, MuleSoft, Salesforce Data Cloud, Low Code, Emerging Data and AI platforms, with an agnostic approach
  • Data integration and orchestration at scale
  • AI automation and responsible deployment
  • Real-world case studies across financial services, Retail, Utils, Healthcare, Government, and AI-tech

***

### 🧠 Topic 1: From Data Chaos to Strategy – Building Foundations for AI

Sub-questions:

  • What are the most common blockers to becoming “AI-ready” across large organisations?
  • Is centralised data governance still relevant, or should we embrace decentralised, domain-led models (e.g. Data Mesh)?
  • How do you get buy-in for foundational data investment when the business wants "quick wins" in AI?
  • What does a realistic 12-month roadmap to AI capability look like?
  • When is too much data a problem, and how do you simplify?

***

### 🛠 Topic 2: Real-World Data Integration – Breaking Silos with APIs, Events & Modern Platforms

Sub-questions:

  • MuleSoft, Confluent, Fabric, Data Cloud, Microsoft, Agentic Platforms and others - how do you choose the right tool for the job?
  • What does “real-time” really mean in business use cases, and where does batch still win?
  • What are the key lessons learned from large-scale integration projects across government and finance?
  • How do you balance short-term delivery with long-term platform thinking?
  • When should you embed integration into product teams vs centralising it?

***

### 🤖 Topic 3: Responsible AI – Delivering Innovation Without the Hype

Sub-questions:

  • What frameworks or checks do you use to validate AI use cases before delivery?
  • How do you manage risk when your AI system impacts customers or citizens?
  • What should every data leader understand about explainability and compliance?
  • Is GenAI ready for real enterprise use, or is it still a prototype play?
  • What should boards and execs be asking before signing off on AI investments?

***

### 📈 Topic 4: Scaling What Works – Turning Pilot Projects into Sustainable Success

Sub-questions:

  • Why do so many proof-of-concepts fail to scale in enterprise settings?
  • What does it take to embed analytics and automation into day-to-day operations?
  • What KPIs actually matter when measuring success in AI/data initiatives?
  • Should AI/data teams report into IT, the business, or stand alone?
  • How do you retain talent and momentum after the "initial hype" fades?

🎟️ Spaces are limited and filling fast – RSVP or update your status now.
We have an extensive waitlist and would love to offer any available spots to others in the community.

Temas relacionados

SaaS (Software as a Service)
Big Data
API
Application Development
Microsoft

También te puede gustar