31 episodes

Leaders of Analytics is a podcast about data-driven decision-making, modern business leadership and the use of data and artificial intelligence in business and society.

Leaders of Analytics Jonas Christensen

    • Business
    • 5.0 • 2 Ratings

Leaders of Analytics is a podcast about data-driven decision-making, modern business leadership and the use of data and artificial intelligence in business and society.

    The Future of Analytics Tech with Benn Stancil

    The Future of Analytics Tech with Benn Stancil

    Every company, regardless of size, is dealing with a barrage of data. In any typical organisation, there is more information on hand than we know how to use or manage.

    While every team in the organisation is screaming for analytics professionals to turn data into insight, a strong data and analytics tech stack is foundational to being able to make sense of it all.

    The need for a robust and efficient data and analytics tech stack has created a sprawling industry for new technology solutions that sell the promise of seamless integration and faster insights.

    Today, there are a plethora of data and analytics platforms available, most with very high valuations attached to them.

    But do we really need all these tools to make us super-powered data users?

    To answer this question and many more related to the data and analytics tech stack, I recently spoke to Benn Stancil.

    Benn is the co-founder and Chief Analytics Officer at Mode. Mode is a modern analytics and BI solution that combines SQL, Python, R and visual analysis to answer questions for its users.

    In this episode of Leaders of Analytics, you will learn:

    What the perfect analytics tech stack looks like and why.
    Programmatic automation of the analytics workflow.
    What will cutting-edge analytics tech be able to do 5-10 years from now.
    Why Been thinks the Chief Analytics Officer role should be redefined, and much more.

    Connect with Benn

    Benn on LinkedIn: https://www.linkedin.com/in/benn-stancil/

    Benn on Twitter: https://twitter.com/bennstancil

    Benn's (brilliant) Substack blog: https://benn.substack.com/

    • 48 min
    Creating a Better Data Warehouse with the Unified Star Schema, Featuring Francesco Puppini

    Creating a Better Data Warehouse with the Unified Star Schema, Featuring Francesco Puppini

    In a recent conversation with data warehousing legend Bill Inmon, I learned about a new way to structure your data warehouse and self-service BI environment called the Unified Star Schema.

    The Unified Star Schema is potentially a small revolution for data analysts and business users as it allows them to easily join tables in a data warehouse or BI platform through a bridge.

    This gives users the ability to spend time and effort on discovering insights rather than dealing with data connectivity challenges and joining pitfalls.

    Behind this deceptively simple and ingenious invention is author and data modelling innovator Francesco Puppini.

    Francesco and Bill have co-written the book ‘The Unified Star Schema: An Agile and Resilient Approach to Data Warehouse and Analytics Design’ to allow data modellers around the world to take advantage of the Unified Star Schema and its possibilities.

    Listen to this episode of Leaders of Analytics, where we explore:

    What the Unified Star Schema is and why we need it
    How Francesco came up with the concept of the USS
    Real-life examples of how to use the USS
    The benefits of a USS over a traditional star schema galaxy
    How Francesco sees the USS and data warehousing evolving in the next 5-10 years to keep up with new demands in data science and AI, and much more.

    Connect with Francesco

    Francesco on Linkedin: https://www.linkedin.com/in/francescopuppini/

    Francesco's book on the USS: https://www.goodreads.com/author/show/20792240.Francesco_Puppini

    • 47 min
    Building Impactful Analytics Teams with John Thompson

    Building Impactful Analytics Teams with John Thompson

    Modern analytics teams are central business functions directly and indirectly responsible for increasing revenue, reducing costs, optimising processes and improving customer and employee satisfaction.

    But there are many obstacles along the way. Data needs collecting, projects need careful design and execution and stakeholders need convincing. Analytics teams are required to cover a wide range of technical knowledge, business acumen and leadership skills to be impactful.

    What is the recipe for creating analytics teams that deliver impactful solutions and drive real business value? What are the technical, interpersonal and leadership skills required to lead the business through change and adoption of analytics?

    To answer these questions, and many more relating to the art and science of building excellent analytics functions, I recently spoke to John K. Thompson.

    John is an international data and technology executive with over 30 years of experience in business intelligence and advanced analytics and author of the best-seller ‘Building Analytics Teams’.

    In this episode of Leaders of Analytics, we discuss:

    The hallmarks of an excellent analytics team
    What a perfect analytics team looks like
    The skills, personality traits and behaviours you need in an analytics team
    The common traits of highly effective analytics leaders
    How analytics leaders set themselves up to meet the expectations of business stakeholders
    How to select and prioritise the right projects to work on
    Where organisations typically fail when designing analytics teams
    The lowdown on John’s upcoming book, and much more.

    John on LinkedIn: https://www.linkedin.com/in/johnkthompson/

    John's book 'Building Analytics Teams': https://www.packtpub.com/product/building-analytics-teams/9781800203167

    • 49 min
    Ultralearning: How to Master Hard Skills and Accelerate Your Career with Scott Young

    Ultralearning: How to Master Hard Skills and Accelerate Your Career with Scott Young

    There is so much to learn!

    If you’re anything like me, you’re overwhelmed by the number of books, articles, podcasts, online and offline courses, webinars and other training opportunities out there.

    Today, we’re not short of learning materials, but often lack the time and capacity to learn new things.

    But what if there’s a better way to learn?

    Enter the concept of “Ultralearning”, coined by best-selling author Scott Young.

    A few years ago, I read Scott’s book Ultralearning and it changed my life. Not only did Scott’s approach to learning increase my learning rate significantly, it also made the process a lot more enjoyable overall! 

    Scott is an impressive Ultralearner who has used his advanced learning strategies to complete a 4-year computer science degree in 12 months, learn languages such as Spanish, Chinese, Korean and Macedonian and become a decent portrait artist.

    And then he’s written a book about it.

    In this episode of Leaders of Analytics, you will learn:

    How Scott has used his learning principles to master very complex and diverse skills in a very short time
    How we learn and retain information
    How we can structure our learning to faster absorption and better retention
    How Scott designs a learning strategy from scratch
    Whether Malcolm Gladwell’s “10,000 hour rule” is true or BS
    Strategies for learning hard and soft skills, and much more.

    Scott's website (full of excellent learning resources): https://www.scotthyoung.com/

    Scott's podcast: https://www.scotthyoung.com/blog/podcast/

    Scott on Twitter: https://twitter.com/scotthyoung/

    Scott on LinkedIn: https://www.linkedin.com/in/scott-h-young-867ab21/

    • 59 min
    How to Turn Your Textual Data Into a Goldmine with Bill Inmon

    How to Turn Your Textual Data Into a Goldmine with Bill Inmon

    An estimated 80 to 90 percent of the data in an enterprise is text. Sadly, this rich information is mostly neglected for analytical purposes.

    Textual data is typically full of information, but also very complex to interpret computationally and statistically. Why?

    Because textual data is both content and context. The same words and sentences can have very different meanings depending on the context.

    Textual data is truly a goldmine, but how can we mine it without being digital superpowers like Google, Microsoft or Facebook?

    To answer this question and many more relating to interpretation of textual data, I recently spoke to Bill Inmon.

    Bill is the Founder, Chairman and CEO of Forest Rim Technology and author of more than 60 books on data warehousing. He is often described as the Father of Data Warehousing due to his pioneering efforts in making data and data technologies available to organisations across all industries and sizes.

    In this episode of Leaders of Analytics, we discuss:

    How Bill became the Father of Data Warehousing
    The history of data warehousing and the most exciting developments in this space today
    The typical challenges holding us back from extracting value from textual data
    The concept of the “Textual ETL” and it’s benefits over other text data storage and analytics approaches
    Why NLP is not the best approach for textual data analytics
    The biggest opportunities for textual analytics today and in the future, and much more.

    Connect with Bill:

    Forest Rim Technnology: https://www.forestrimtech.com/

    Bill on LinkedIn: https://www.linkedin.com/in/billinmon/

    • 50 min
    The Future of Data-Driven Personalised Healthcare featuring Felipe Flores

    The Future of Data-Driven Personalised Healthcare featuring Felipe Flores

    This is the second episode of a two-part series of Leaders of Analytics featuring global data science thought leader and influencer Felipe Flores.

    Felipe is a global thought leader and influencer in the field of data science and artificial intelligence.

    He is the founder of Data Futurology – a podcast and events company with more than 10,000 weekly listeners, Head of Data & Technology at Honeysuckle Health and co-organiser of Data Science Melbourne.

    In this episode we discuss:

    Felipe’s work at Honeysuckle Health
    What Honeysuckle Health does and why the company was founded by two large insurance organisations
    How data-driven personalised health care works in practice and the typical outcomes patients see

    How data will be used to drive positive health outcomes in the future, and much more.

    • 42 min

Customer Reviews

5.0 out of 5
2 Ratings

2 Ratings

TheLPMaster8 ,

Great podcast!

"Great host, great guests, and great discussions on all things data. Would definitely recommend this podcast."

datainsight ,

Timely and relevant

Jonas puts enormous thought into every one of the episodes geared towards bringing out the best from his guests to share. I strongly recommend the podcast to anyone interested in the field or looking to enter it.

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