Usman Shahbaz

With AI, now more than ever, data governance matters. Join the Data Governance for Leaders Course in Sydney at AGSM @ UNSW Business School! Join me to find out how to build a sound platform to turn information into insights and fuel better decision-making with AGSM's exclusive Data Governance for Leaders course! This course will equip you with the knowledge and tools to: * Build a strong business case for data governance. * Navigate the key principles and frameworks. * Design effective data governance teams and projects. * Champion a data-driven culture within your organisation. Stop struggling with data and start thriving with it! Enrol today and unlock the hidden potential of your organisation's data. (gif thanks 🙏 to someone who I grabbed it from then they disappeared from my feed - please ping me if it was you) https://lnkd.in/gbMx6d4Y Limited seats available! Register now for the Data Governance for Leaders course. #datagoverance #leaders #data #ai

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🎙 Lead with Data Podcast - Season 4 - Episode 22 - “The Evolving Data Scientist in an AI-Driven World" with Dr M Maruf Hossain, PhD https://lnkd.in/gtq3Q8Ks A question that comes up often is whether the role of a Data Scientist is changing or disappearing in the age of AI. To unpack this, I’m excited to welcome Dr M Maruf Hossain, PhD, one of the Global Top 100 Innovators in Data and Analytics 2024. As a pioneering leader in AI and data science in Australia, Dr. Hossain has delivered tangible business value across startups, enterprises, consulting firms, and government agencies. With a PhD in AI from The University of Melbourne, a master’s in software engineering, an Honours in Mathematics and impressive career into Data Science Leadership, he’s more than qualified to discuss this topic. In this episode, we discuss the evolving role of data scientists in an AI-driven world, discussing key shifts in skills, collaboration, and the impact of automation and no-code tools.   🎧 Tune in to hear insights on the future of data science and how professionals can stay ahead of emerging trends and technologies. Apple podcast : https://lnkd.in/gZv-vynQ Spotify: https://lnkd.in/gSEdCPAv

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📢 Hey friends of Data Sciences and Machine Learning, I'm looking for a speaker for Perth Machine Learning Group to share ideas, learnings, experiments and knowledge for the August Meetup (In-person). DM me for more details. If you have a vague idea of what you might want to present, ping me anyway! I'll help you polish it! #AI #ML #LLM #SpeakingOpportunity

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Like the metaphor and have used this comparative as well, with #data being my gauges, dashboards, indicators, and VR Vision Pro heads up display. #AI is my copilot, which I trust , but always verify. My hands 🙌 on the wheel, feet on the pedals, and eyes 👀 all around are making the decisions needed at breakneck speed. Ideally, I still have a human copilot, but they would be jacked into the #GAI matrix. #datamatters #peoplemattermost #dataninjashorts from YOUR #dataninja

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Going to skip my daily NIST AI Risk Management Framework post today and instead share a podcast I've just found: Everyday AI by CSIRO, hosted by CSIRO's Data61 director Jon Whittle. As someone who proudly worked for NICTA in mid-2010s, right when it was being merged into @CSIRO's Data61, I was very excited to find this podcast and cannot wait to listen to all its episodes - because what a great list of topics it covers: AI in pregnancy and early years, AI in parenting, AI and the end of life...and beyond! Link in the comments, trust me - this is going to be great! #AI

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I get asked on a regular basis what we see happening in the market on Gen AI. Which industries and which use cases are being put in production? What’s the ROI? 🧠 Knowledge systems - are one of the most common use cases where experimentation is moving on into productionisation. Think market analysis and summarisation, policy documents and customer service. 🏭 Gen AI Factory - Many enterprise size organisations have realised the use cases are still unclear but the sheer number of Gen AI usage and experimentation is warranting a secure foundational platform to experiment, deploy and manage Gen AI on. Hyperscalers have rapidly mature their offerings in this space to enable this (even in 🇦🇺 yay!) At Mantel Group, we both help our clients prioritise, evaluate and productionise Gen AI use cases, as well as set up the LLMOps foundations to build the next set of use cases in a secure and responsible way. Check us out if you need expertise! https://lnkd.in/g2qPgbCe

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I just recently completed the course on "Build and Execute an Organisational AI Strategy"! This was a nice course for anyone looking to acquire a general overview of AI strategy. It provided valuable insights into AI governance frameworks such the Hourglass Model and helped me understand how to effectively implement AI in an organisational context considering the practical actions to reimagine business and technology with Generative AI. #AI #GenAI #Strategy #Governance #LifelongLearning #Coursera

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Major news flash: leveraging part of Google’s $1B Digital Futures Initiative we just signed a 1-plus-1-equals-15 deal. Bringing together the two AI and Science powerhouses CSIRO and Google, this partnership will be an inflection point in AI-powered scientific discovery. Press releases with more info here: Google: https://lnkd.in/gDxbsR4b CSIRO: https://lnkd.in/gG2EyqMz Professionally speaking, for my whole career I’ve been passionate about two things more than about anything else- and by far at that: #science and #AI. Can you imagine the enthusiasm I’m feeling at this moment about getting to marry the two so spectacularly…we only got here because of so many others who share that enthusiasm and determination - just calling out a few names on both sides of the aisle: Jon Whittle Scott Riddle Astitva Chopra Heather Tompkins LINDA ALLARD Dr Rebecca Michael Eliza Keck Alison Donnellan Grace Chung Melanie Silva - and thank you to many more whose relentless work has made this possible, you know who you are. To all scientists out there: don’t just watch this space: get in touch and check out the links in the press releases - you do NOT need to be an AI expert or seasoned data scientist to have fun at this party…this is for all scientists and we’re just getting started!! Nicholas Thompson Cade Metz Melissa Heikkilä Mike Cherney https://lnkd.in/giitUt7E

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After 2 weeks of meeting top execs and data scientists, too many people still get this wrong. As part of the Why Data Science Projects Fail book tour with Doug Gray in Australia, I kept noticing one part of people's expectations around data science projects was still wrong, and it was the most basic part: What to expect from a data science tool. This message was hammered home after last week's trip when I finished reading John Hawkins' great book, Getting Data Science Done. John's book summarised it beautifully when he wrote: A data scientist's job is helping people who don’t really understand data to make better decisions using data. This comment resonated wonderfully with me as it aligns with a message I tell students in my BSAN4201 course at UQ: We are not searching for the right answer, we are helping someone make a decision. And this is what most people get wrong. They expect that data scientists provide them with "the answer". This "answer" should supposedly fully solve their problem, but it can't - a data scientist builds a model, not reality. It is one piece of the puzzle that helps make a decision. It is also worth mentioning that John's book is complementary to Doug and my book Why Data Science Projects Fail. Where we take an organisation's view of data science projects (and touch on what it means for data scientists), John's book takes a data scientists view of projects in the organisation and what data scientists need to do to succeed. A good pair of books to read. #whydatascienceprojectsfail #datascience #ai #artificialintelligence #AIfail

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CSIRO writes "Everyday AI: Artificial intelligence in pregnancy and the early years - AI is breaking new ground in the earliest stages of our lives, revolutionising fertility care and improving the wellbeing of premature babies by enabling early detection of developmental challenges." https://lnkd.in/eF2i5cj4. #artificialintelligence #pregnancy #earlyyears #fertilitycare #revolution #healthcare #csiro

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AI CEOs: A Ponderous Perspective on the Future of Corporate Control? This is an excellent, thought-provoking piece. Can AI replace top-tier executives? The University of Waikato Ethics Professor Nick Agar suggests a future where AI algorithms, not humans, occupy the corner offices. The rising CEO salaries prompt the question: Is automation the future of leadership? https://lnkd.in/gv24pwJR AI's capability to learn complex tasks, like driving, could extend to a corporate setting. An AI CEO could potentially outperform human decision-making, pushing companies to new efficiency heights. However, this vision stirs complex questions: What principles will guide AI leaders - relentless profit or societal good? #AIinLeadership #FutureOfCorporate #Automation #AIExecutives #AIandEthics #AIefficiency #AIforGood #LeadershipInnovation

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Behaviour vs Surveys? Well there was a lot of hope and resulting hype when this poll appeared prior to the election. Now we know it was BS. Sadly this demonstrates how wrong people can get using survey data. https://lnkd.in/gtvWYE6r #analytics #data #pollsters

AI and autonomous everything - some more thoughts on how AI will be used in business. Some thoughts arising from the Informa #FEI2024 Conference https://lnkd.in/gyb-thHY

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Picking randomly from my last post on favourable data-to-value conditions, here’s an expansion (a la GPT) on principle #6: ‘Applications that Externalize Data as a Product and Internalize the Dollar Cost of Associated Data Work’. ******** This principle emphasizes making data easily accessible for the organization while absorbing the costs and efforts associated with data management internally. Here’s an explanation: ### Externalizing Data as a Product - **Data as a Product**: Ensuring data is well-organized, documented, and accessible via APIs, data streams, or other mechanisms. - **Usability and Accessibility**: Standardizing formats and documentation to make data consumable and useful, enhancing data-driven decision-making. - **Interoperability**: Promoting integration across systems within the organization, allowing departments to use data effectively for analytics and decision-making. ### Internalizing the Dollar Cost of Associated Data Work - **Cost Management**: Application run and change TCO cover costs related to data preparation, management, storage, and processing internally, including data cleaning, transformation, storage infrastructure, and quality assurance. - **Operational Efficiency**: Optimizing data-related tasks within the application’s management envelope to reduce redundancy and avoid unexpected costs elsewhere in the organization. - **Data Governance**: Controlling the data lifecycle within the application’s accountability & responsibility envelope, to ensure fitness for purposes and consistent availability while optimizing resources and expenses. ### Contrast with the Opposite Approach - **Externalizing Costs, Internalizing Data**: This alternative involves data remaining siloed within applications, requiring other parts of the organization to intermediate, bearing the costs and effort of extraction, processing, and management. This can lead to inconsistencies, inefficiencies, and higher overall costs to the organisation. ### Example - **Externalizing Data as a Product**: A CRM system makes fit-for-purpose customer interaction data accessible via standardized APIs for marketing, sales, and support teams. - **Internalizing the Dollar Cost of Data Work**: The CRM system handles all data processing and management tasks within its budget. ### Summary This principle advocates for making data accessible across the organization while managing the costs and efforts of data preparation within the application. This approach ensures standardized, high-quality data, optimizing resource use and cost management, and leading to improved efficiency in data utilization across the firm. ******** See the rest of the principles here: https://lnkd.in/ejwn4-eU #datagovernance #techgovernance #systems

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Over the years as a Chief Data & Analytics Officer, it has become evident to me that CDAO's lack the essential support systems needed to be successful when compared to roles like CEO, CIO, and CFO. This lack of support and role clarity lead to challenges and a short "life expectancy" of around two years for CDAO's at most companies. Having driven Data and AI transformations at various companies, I have experienced this lack of support system myself. To help address this gap, I am launching a series titled "Ask me anything about data," where I will share my experiences and insights in this domain. I will be focusing on content and discussions through 1-2 minute video responses to each question I receive. While the video quality may not be professional, the aim is to add value through sharing experiences and fostering discussions. Feel free to email me at williamgroves@yahoo.com or bill.groves@bain.com with any questions you have about data! The first question I a, often asked is: Why do data transformations fail, and what are the key factors for success?

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I am looking forward to attending the Gartner Data & Analytics Summit in Sydney next week. Keen to hear from some industry leaders what is happening in the AI space. Particularly looking forward to the talk from Lydia Jones on The Ethics of D&A and AI: Navigating Common Dilemmas #datascience #dataengineer #LLMs #dataethics

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#DataFam, Have you heard of LaDataViz? https://lnkd.in/gVpeuUdH Tristan Guillevin has been a great source of inspiration for me. I recently played around with LaDataViz AdvViz export capability. Yet another workshop at #NLTwithCoachAndy (Andy Kriebel) I find these capabilities fancy, yet useful if you are looking for that 'aha' experience while working with Tableau. Let's silence those who believe #Data is boring. Check out the interactive version on #TableauPublic https://lnkd.in/gCY_kGaY

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The Code.Sydney Gen AI Study Group was successfully kicked off tonight with Module 1 - Fundamentals. We went through the overview of the material and the fundamentals in preparation for Module 2 where we actually start interacting with an LLM with Python, on our way to build our very own Generative AI knowledge base search chatbot. For those that registered, but were unable to attend, we have a recording available, so you can follow at your own pace. https://buff.ly/3YbjGpk Finally, you can now RSVP for Module 2 (Thu, 25th July 6:00 to 6:30PM). See you there! https://buff.ly/4f2doOZ ~~~ PS. I regularly share tips and ideas on software development, applied machine learning and Generative AI. If these are the type of topics you want to hear about, please connect with me!

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