A twice-monthly podcast for businesses looking to maximise the value of their data and data teams. Learn from business leaders and experienced data professional...
Episode 52: Automating the Automators – How AI and ML are Transforming Data Teams
Genevieve Hayes Consulting
Episode 52: Automating the Automators – How AI and ML are Transforming Data Teams
In many organisations, data scientists and data engineers exist as support staff. Data engineers are there to make data accessible to data scientists and data analysts, and data scientists are there to make use of that data to support the rest of the business.But in helping everyone else in the business, data professionals can often forget to help themselves.However, just as AI and machine learning can be used to help others in the organisation perform their jobs more effectively, there’s no reason why they can’t also be used to help data professionals excel in their own jobs. And as experts in applying these techniques, data scientists are perfectly placed to leverage them.In this episode, Prof Barzan Mozafari joins Dr Genevieve Hayes to discuss how AI and machine learning are helping data professionals do their jobs more effectively.
Guest Bio
Prof. Barzan Mozafari is the co-founder and CEO of Keebo, a turn-key data learning platform for automating and accelerating enterprise analytics. He is also an Associate Professor of Computer Science at the University of Michigan and Prof. Barzan Mozafari is the co-founder and CEO of Keebo, a turn-key data learning platform for automating and accelerating enterprise analytics. He is also an Associate Professor of Computer Science at the University of Michigan and has won several awards for his research at the intersection of machine learning and database systems.
Highlights
(00:05) Meet Barzan Mozafari(00:50) The role of AI in data engineering(01:36) The birth of Keebo(02:34) Challenges in modern data pipelines(05:41) How Keebo optimizes data warehousing(07:35) AI and ML techniques behind Keebo(08:47) Reinforcement learning in practice(16:23) Guardrails and safeguards in AI systems(26:29) The build vs. buy dilemma(36:03) Future trends in data science and AI(39:36) Final advice for data scientists(40:50) Closing remarks and contact information
Links
Keebo websiteConnect with Barzan on LinkedIn
Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE
The post Episode 52: Automating the Automators – How AI and ML are Transforming Data Teams first appeared on Genevieve Hayes Consulting and is written by Dr Genevieve Hayes.
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Episode 51: Data Storytelling in Virtual Reality
Genevieve Hayes Consulting
Episode 51: Data Storytelling in Virtual Reality
In the 2002 movie, Minority Report, the future of data interaction is depicted as Tom Cruise standing in front of a computer monitor and literally grabbing data points with his hands. Data interaction is shown to be as easy as interacting with physical objects in the real world.This vision of a world where data is accessible to all was considered to be science fiction when Minority Report was first released. But over 20 years later, we are now at a point where technology has become good enough for this to soon become fact. And its data science that’s making this possible.Or more accurately, it’s the intersection of data science and art.In this episode, Michela Ledwidge joins Dr Genevieve Hayes to discuss how virtual reality and data science can be combined to create interactive data storytelling experiences.
Guest Bio
Michela Ledwidge is the co-founder and CEO of Mod, a studio specialising in real-time and virtual production, and the creator of Grapho, a VR platform that lets non-technical users examine and manipulate graph data. She is also the writer and director of A Clever Label, a world-first interactive documentary.
Highlights
(00:05) Meet Michela Ledwidge(02:04) Michela’s journey from Commodore 64 to interactive filmmaking(06:40) The birth of Mod and remixable films(14:48) Exploring graph databases and data science techniques(25:33) The future of data science and AI in creative industries(32:27) Grapho: Data science + storytelling in virtual reality(48:29) The future of data science and storytelling(49:37) Conclusion and contact information
Links
Grapho website
Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE
The post Episode 51: Data Storytelling in Virtual Reality first appeared on Genevieve Hayes Consulting and is written by Dr Genevieve Hayes.
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50:27
Episode 50: Addressing the Unknown Unknowns in Data-Driven Decision Making
When it comes to awareness and understanding, what we know and don’t know can be split into four categories: known knowns; unknown knowns; known unknowns; and unknown unknowns. And to quote former US Secretary of Defence Donald Rumsfeld: “If one looks throughout the history of our country and other free countries, it is the latter category that tends to be the difficult ones.”
When Rumsfeld made his famous “unknown unknowns” speech, he was referring to military intelligence. But the concept of “unknown unknowns” is just as relevant to data and data science. Those data dark spots, or data gaps, can be a real issue when it comes to data-driven decision making.
In this episode, Matt O'Mara joins Dr Genevieve Hayes to discuss the challenges and risks data gaps present to businesses and the community, and what data scientists can do to help address this issue.
Guest Bio
Matt O'Mara is the Managing Director of information and insights company Analysis Paralysis and is the founder and Director of i3, which helps organisations use an information lens to realise significant value, increase productivity and achieve business outcomes. He is also an international speaker, facilitator and strategist and is the first and only New Zealander to attain Records and Information Management Practitioners Alliance (RIMPA) Global certified Fellow status.
Highlights
(00:55) Understanding information gaps
(02:33) Matt O'Mara's journey and insights
(04:58) Real-world examples of information gaps
(07:30) The impact of information gaps on society
(11:54) Organizational challenges and solutions
(25:55) Critical information sources and management
(31:33) Developing an information lens
(42:47) The role of data scientists in addressing information gaps
(45:29) Conclusion and contact information
Links
i3 website
Connect with Matt on LinkedIn
Connect with Genevieve on LinkedIn
Be among the first to hear about the release of each new podcast episode by signing up HERE
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46:08
Episode 49: AI-Generated Advertising and the Future of Content Creation
Genevieve Hayes Consulting
Episode 49: AI-Generated Advertising and the Future of Content Creation
The idea of targeted marketing is nothing new. Even before the advent of computers and data science, businesses have always tried to optimise their advertising campaigns by tailoring their advertisements to their ideal buyers.Data science allowed businesses to become more effective at this targeting. However, it was still necessary for businesses to manually create the advertising content they wanted to share with their target buyers. That is, until recently.In this episode, Hikari Senju joins Dr Genevieve Hayes to discuss how advances in AI technology have made it possible to generate personalised advertising content, optimised to produce the best results, and what that means for content creators.
Guest Bio
Hikari Senju is the founder and CEO of Omneky, an AI platform that generates, analyzes and optimizes personalised advertising content at scale. He is a Harvard computer science graduate and also co-founded tutoring app Quickhelp, which he later sold to Yup.com.
Highlights
(02:06) How OmneKey works(03:29) Personalisation in advertising(06:35) The role of human input in AI-generated content(10:45) Impact of AI on the advertising industry(15:09) Hikari Senju’s journey and insights(19:53) Technical deep dive into OmneKey(25:54) The competitive landscape of AI(32:10) The future of content and AI(40:26) Conclusion and final thoughts
Links
Omnekey websiteConnect with Hikari on LinkedInFollow Hikari on X
Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE
The post Episode 49: AI-Generated Advertising and the Future of Content Creation first appeared on Genevieve Hayes Consulting and is written by Dr Genevieve Hayes.
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42:33
Episode 48: Overcoming the Machine Learning Deployment Challenge
Genevieve Hayes Consulting
Episode 48: Overcoming the Machine Learning Deployment Challenge
It’s been 12 years since Thomas H Davenport and DJ Patil first declared data science to be “the sexiest job of the 21st century” and in that time a lot has changed. Universities have started offering data science degrees; the number of data scientists has grown exponentially; and generative AI technologies, such as Chat-GPT and Dall-E have transformed the world.Yet, throughout that time, one thing has remained the same. Most machine learning projects still fail to deploy.However, it’s not the technical capabilities of data scientists that let them down – those are now better than ever before. Rather, “it’s the lack of a well-established business practice that is almost always to blame.”In this episode, Dr Eric Siegel joins Dr Genevieve Hayes to discuss bizML, the new “gold-standard”, six-step practice he has developed “for ushering machine learning projects from conception to deployment.”
Guest Bio
Dr Eric Siegel is a leading machine learning consultant and the CEO and co-founder of Gooder AI. He is also the founder of the long-running Machine Learning Week conference series; author of the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die and the recently released The AI Playbook; and host of The Dr Data Show podcast.
Highlights
(01:21) Challenges in machine learning deployment(05:00) The importance of business involvement in ML projects(15:39) Defining bizML and its steps(25:32) Understanding predictive analytics(26:52) Challenges in model deployment and MLOps(29:12) BizML for generative and causal AI(31:25) Exploring uplift modeling(35:45) Gooder AI: bridging the gap between data science and business value(45:45) Beta testing and future plans for Gooder AI(47:35) Final advice for data scientistsb
Links
BizML website
Connect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE
The post Episode 48: Overcoming the Machine Learning Deployment Challenge first appeared on Genevieve Hayes Consulting and is written by Dr Genevieve Hayes.
A twice-monthly podcast for businesses looking to maximise the value of their data and data teams. Learn from business leaders and experienced data professionals how to use data science to create business value, and grow your in-house data capabilities.
Visit the show's website at: www.genevievehayes.com
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