Kelli Dudley

Data is the new electricity - but only if it's trusted, governed and delivered at scale. Discover how NAB is transforming its data strategy to drive innovation, compliance and customer-centricity across Australia and New Zealand. In this on-demand webinar, learn how NAB is working with Collibra and Databricks to: ✨ Modernize their data foundation ✨ Embed governance at scale ✨ Deliver trusted, actionable insights Watch now to see how NAB is treating data like electricity - essential, reliable and safely delivered. https://ow.ly/7SBw50VNeRq

9

Snowflake Intelligence is Snowflake’s conversational AI experience that lets your teams ask questions in plain language and get trusted answers from governed data and documents, without writing SQL. As a Snowflake Elite Partner and APAC launch partner for Snowflake Intelligence, Billigence helps organisations design and deploy secure, production-ready assistants that fit their governance, data model and business priorities. We’ve already delivered real outcomes with Snowflake Intelligence – from finance narratives and regulatory policy assistants to our own internal HR policy chatbot that gives employees instant, cited answers from curated documents. 👉 Read more about how it works, where Snowflake Intelligence fits in your AI journey and how Billigence can help: https://lnkd.in/gYyQj6cq

35

3 Comments

I keep hearing the same thing in Australian boardrooms: AI won’t deliver without strong data foundations. A new MIT Technology Review Insights survey confirms it — 45% of leaders say data integration is the top challenge, 44% point to governance/security. In government it’s as high as 95% . For me, the message is simple: AI success starts with responsible data governance. Without clean, secure, trusted data, even the best models can’t scale. How is your organisation embedding governance into its AI journey? #DataGovernance #AI #Australia #Leadership

6

An important update for colleagues delivering #datagovernance here in NZ: the guidance for Māori data associated to the new Information Sharing Standard has now dropped. When the initial guidance came out the Māori data governance requirements embedded in the new standard led to a few second order questions. The initial supporting guidance developed the material in the standard, but that was only provisional. That guidance has since been chopped up into sections and expanded, E.g model legal clauses for updating contracts. I started analysing the implications of the four small rules in the standard in the beginning of June and only concluded about three weeks ago. Aka the implications are significant for the existing body of data governance regimes (broadly understood). Furthermore, the expectations are embedded in the standard so we can't pick and choose the bits we like/agree with and treat the remainder as optional Fortunately there are pathways to making all the various regimes synchronise but obtaining that solution necessitates changes in the order of operations (there is a BEDMAS for data governance). Usefully the standard elevates the Te Kāhui Raraunga framework up a level and that excellent body of work helps with the reframing and reordering.

31

2 Comments

What Data & AI tools and skillsets are in demand this year? 🧐 Kicking it off for 2026 🕺🏼 AUSTRALIA 🦘 🔵 🟡 Microsoft Fabric, completed end to end implementations are what really set you apart 🔵 🟡 Copilot, hands on experience with a commercial rollout, not just POCs 🔵 🟡 Databricks, no surprises here, demand remains strong NZ 🥝 🔵 🟡 Snowflake, still leading for cloud data platforms, particularly in mature environments Across the board: 🔵 🟡 Strong problem solving ability and business acumen matter more than ever. 🔵 🟡 The days of being purely tool focused are over. 🔵 🟡 Power BI as the data visualisation tool of choice, particularly in Microsoft centric environments I'm also seeing continued demand for: 🔵 🟡 Analytics Engineers who can bridge data engineering and business insights 🔵 🟡 ML / Software Engineers who can take models beyond experimentation and into production If you can get hands on with any of these tools or have the chance to build these skills in a commercial environment, take it! The Data & AI market keeps evolving and everything above could change quickly. Watch this space 👀 #Data #AI #recruitment #demand #skills #tools #Australia #NewZealand

59

1 Comment

Last week I had the opportunity to be at the Gartner's Data and AI Summit at Sydney. The bread and butter of Gartner's is to research the industry and introduce workable frameworks, and man, they did deliver. So many areas we follow with our intuition rather blindly, they had crystal clear frameworks. Be it identifying business opportunities for AI and development of solid, tracking business cases, be it having your data ready for AI applications, AI governance or when to set your AI agents free. These sessions did cover most that is essential, easing ourselves not to keep scratching our heads when making technical or business decisions related to AI.

49

Today, one of the founders of Databricks, Arsalan Tavakoli was in Sydney (maybe one day we will get someone to visit Perth) and spoke to the team about where Databricks is heading, especially after the success of the Data and AI Summit last week. One thing that really stood out to me as a Field Engineer is the concept of "pull based enablement", or "just-in-time learning" (everything has to be named based off an engineering concept these days). It's this approach that you don't need to know everything right now, and it's actually impossible with the rate that Databricks is growing to even try. Rather, it's better to learn what you need for your customers right now, and use that knowledge to help them succeed. And when something new comes up that they need, you go out and do the training, or read the documentation, or listen to the presentation, and then you are equipped with the knowledge to solve that next problem that is in front of you. As someone fairly new to Databricks, this resonated with me, as I feel that the first three months have been a lot of training but I have barely scratched the surface, and maybe that is ok as long as I can deliver for the customers that are in front of me right now. #LifeatDatabricks #Brickster #SolutionArchitect

73

2 Comments

Are data scientists going extinct? 🦖 This week on The Small Business CTO podcast, we have a very special guest and top bloke - Douglas Robertson of DR Analytics Recruitment! As a leader in data recruitment, Doug and I had a great chat about building effective data teams, the future of data roles, and the power of data in business decision-making. Episode drops later this week 🔥

34

9 Comments

According to new research from Amplitude, many Australian professionals trust their gut more than their data when making decisions. Why is this still happening in 2025?! The answer lies in the barriers to getting started. Analytics products can be complicated, and people don't have enough time to learn how to use yet another tool. The good news? It doesn’t have to be that way. By simplifying analytics products into one simple, consolidated platform, and providing the education you need to get started, relying on data can be easy. Learn more: https://lnkd.in/g7Ja6qV5 #leadership #strategy #data #datadecisions #productanalytics #customercentric #operatingmodel #plg #growth #marketinganalytics #customerdata #jtbd #productmanagement #datadriven

10

3 Comments

🇦🇺 Thrilled to share this piece in the The Australian Financial Review by Tess Bennett about Sovereign Australia AI and the journey we're embarking on to build Australis - Australia's own foundational language model. I couldn’t be prouder to be building this alongside my mate and Co-Founder Simon Kriss This isn't just about building another AI model. It's about ensuring Australia maintains its digital sovereignty and voice in an increasingly AI-driven world. We shouldn't be dependent on decisions made in Washington, Silicon Valley, Beijing or Europe about how AI understands and represents our Australian culture, values, and way of life. Yet to achieve this isn’t easy and it takes scale to compete, so we’ve made a massive investment in compute and have acquired 256 NVIDIA Blackwell B200 GPUs hosted in NEXTDC's secure Australian data centre in Melbourne, and managed by our colleagues at SHARON AI What makes me particularly proud of what we’ve done so far: ✅ Ethical from the ground up - We're committing $10M to compensate copyright owners, working WITH creators rather than against them ✅ Built for Australia, by Australians - From the ground up, built, trained and inferenced onshore, here in Australia, and compliant with our privacy and copyright laws ✅ Customers & Partnerships In Place - We partnering with some amazing Aussie organisations to help them solve some of Australia’s AI challenges. The partnerships we can speak about include ACS (Australian Computer Society), UNSW Canberra & GT Systems Australia, with more to follow! The path to digital sovereignty doesn't require billions, it requires vision, ethical principles, and the determination to ensure Australia's voice isn't lost in the global AI conversation. We're proving that sovereign AI can be built responsibly, affordably, and with respect for the creators whose work makes it possible. Australia's digital future should be in Australian hands. Let's build it together. 🚀 Special thanks to Craig Scroggie, Andrew Leece, Kieran Habojan, Dan Mons, Sudarshan Ramachandran, Rhod Brown, Brett Bonser, Melissa Hamilton, Josh Griggs, Rhett Sampson and so many more. #ai #sovereignai #llm #gpt #innovation #australia #australian https://lnkd.in/gnF8N3mR

202

45 Comments

𝑵𝒆𝒘 𝒊𝒏 𝑫𝒂𝒕𝒂 𝑻𝒆𝒄𝒉 𝒘𝒊𝒕𝒉 𝑱𝒖𝒍𝒊𝒂 (𝒃𝒍𝒐𝒈 𝒆𝒅𝒊𝒕𝒊𝒐𝒏) - 𝒁𝒆𝒕𝒂𝒓𝒊𝒔 "𝐈 𝐰𝐢𝐥𝐥 𝐧𝐨𝐭 𝐛𝐮𝐢𝐥𝐝 𝐚𝐧𝐨𝐭𝐡𝐞𝐫 𝐝𝐚𝐭𝐚 𝐰𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞." That was the promise I made to myself as I stepped into a new data leadership role a few years ago. I’ve lived through the pain, the cost, and the delays too many times and I was determined to find another way. Six months later, guess what? I was building another data warehouse. Why? Because given the complexity and the age of legacy data sources there was no other way to get value out of that data without bringing it together, semantically and physically – no federated data platform available at the time would have worked. Now, even with all the tech advances, my clients still hit the same wall: business expects AI magic yesterday, but data is still scattered across cloud, on-prem, and everything in between. And guess what? Running complex queries on disparate data across on-prem and cloud gets really expensive really fast. So now that I have the time to dig into new tools, I’ve been on the lookout for tech that solves the problems I’ve had and keep seeing over and over again in the field. Which brings me to Zetaris. How’s Zetaris different? 1.      It lets you query across platforms without moving the data – yes, we’ve had that before. 2.      But it also has industry models and AI enabled semantic integration– that’s huge, since semantic integration is always a bottleneck. 3.      And it gives you visibility and control over how queries are routed and how much they cost 4.      And it can route the query to the most cost efficient platform for it in real time. It’s essentially a “layer on top” that connects structured and unstructured data, cloud and on-prem, then routes each query to the most efficient engine based on what you're asking.  Zetaris has a Unified Semantic Layer capability that abstracts the raw data from the AI or BI.  This does things like applying masking, obfuscation, encryption, hidden column/tables and applies rules to further protect data. So instead of building a perfect architecture first—you can get value now, then clean up as you go (just don't skip cleaning up - it'll bite you later). To me, that changes the game. Not just technically, but financially as well, especially if you’re worried about runaway compute costs on the cloud. (And let’s be honest—who isn’t?) If you’re wrestling with multi-platform data sprawl, trying to avoid yet another painful warehouse rebuild, or just looking for a smarter path to data and AI value—this is tech worth looking into. Curious to see it in action? You can book a demo: https://lnkd.in/d9E3qEQe or follow Zetaris on LinkedIn to learn more. Anyone here using Zetaris already? Would love to hear about your experience.

22

11 Comments

🔥 Introducing the new season of the Data Tech Talks podcast, this season will deep dive into the journey's of some of Australia's leading data professionals and the unique domain expertise that they have developed over their careers🔥   Raed’s Data Tech Talks Season 2 – Episode 1 – Customer Analytics, Driving Value within the Insurance Domain with Customer Analytics Manager Janani Hari  Listen here: https://lnkd.in/gDN2aDqQ  Spotify: https://lnkd.in/gBtpeACP   Joining me on this episode of Data Tech Talks is Janani Hari, a seasoned data and insights expert in the insurance industry. We explore how customer analytics is reshaping the sector, from improving customer experience to driving data-driven decisions. Janani shares insights on data quality, stakeholder engagement, and the growing role of AI, along with practical advice for aspiring data professionals. #Datatechtalks #Konnectwithdata #konnexusdataanalytics #podcast #insurance #customeranalytics

63

10 Comments

What does ED performance look like beyond “average wait time”? 🏥⏳ I built a privacy-safe Emergency Department analytics dashboard using a synthetic (dummy) dataset that replicates realistic Melbourne hospital workflows (triage categories, wait times, outcomes, and compliance flags). Why synthetic? • Because real ED data is sensitive — and governance + privacy come first. The model is intentionally structured so it can be swapped with real datasets (subject to approvals) from health services and open-data sources. What the dashboard surfaces (sample results from the synthetic dataset): • ED presentations: 2,000 • Avg wait: 64 minutes • P90 wait: 175 minutes (tail delays matter) • % within recommended target: 34% • Admission rate: 61% Why this matters • Averages can look “okay” while worst-case waits (P90) reveal serious operational pressure. This dashboard is designed to help teams quickly answer: • Where are delays concentrated (hospital-level)? • Are we meeting recommended wait targets? • Which triage categories drive demand? • What does the “tail risk” look like? I’d love feedback from anyone working in health ops, analytics, BI, or public-sector data in Australia — and I’m especially keen to learn what additional KPIs would make this more decision-ready. Tagging a few key organizations in the ecosystem: The Royal Melbourne Hospital The Alfred Foundation Monash Health Austin Health St Vincent's Hospital Melbourne The Royal Women's Hospital Northern Health Western Health Eastern Health Peninsula Health The Royal Children's Hospital Peter MacCallum Cancer Centre Epworth HealthCare : GP liaison NSW Health Queensland Health SA Health WA Health ACT Government Health and Community Services Tasmanian Occupational Health & Safety Services Australian Digital Health Agency Australian Institute of Health and Welfare (AIHW) #PowerBI #HealthAnalytics #DataAnalytics #BusinessIntelligence #DataStorytelling #Healthcare #Australia #Melbourne #PublicSector #OperationalAnalytics

16

1 Comment