Jordan Goldmeier, a bestselling author and digital nomad, discusses the underrated role of Excel in data science. He argues that Excel remains relevant due to its versatility and ease of use, especially for non-technical audiences. The conversation touches on the impact of generative AI on Excel's functionality, along with Power Query's ability to simplify data preparation. Goldmeier emphasizes the importance of clear communication in data analysis and shares insights on fostering a data-driven mindset while transitioning to advanced tools.
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insights INSIGHT
Excel's Role in Data Science
Excel is valuable in data science for visually explaining algorithms and creating prototypes.
It allows clear communication of logic and facilitates stakeholder understanding, especially for non-technical audiences.
question_answer ANECDOTE
Excel's Ubiquity
Jordan Goldmeier compares Excel's popularity to the TI-83 calculator, highlighting its widespread use despite potential alternatives.
He emphasizes that technology adoption depends on usage, not idealization, citing the financial system's reliance on Excel.
volunteer_activism ADVICE
Embrace Excel for Communication
Data scientists should learn Excel, especially Power Query, for data cleaning and client communication.
While other tools may be superior for certain tasks, Excel's accessibility and visual interface bridge the gap with non-coders.
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How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning
Jordan Goldmeier
Alex J. Gutman
Becoming a Data Head provides readers with the tools to think statistically, speak intelligently about data, and understand machine learning and AI. It covers the math behind algorithms and common pitfalls in data interpretation, making it accessible to business professionals, engineers, executives, and aspiring data scientists.
Dashboards for Excel
Purnachandra Duggirala
Jordan Goldmeier
This book provides a comprehensive approach to developing dashboards in Excel, covering advanced techniques such as data visualization, dynamic charts, and the use of VBA. It also addresses common pitfalls in dashboard creation and introduces readers to tools like PowerPivot and Power Query.
Data Smart
Jordan Goldmeier
Data Smart is a comprehensive guide that teaches data science using Microsoft Excel, making complex concepts accessible to business professionals. It covers statistics, machine learning, and AI, providing practical solutions for everyday business challenges. The book enhances Excel skills with tools like Power Query and offers real-world applications of data science techniques.
Advanced Excel Essentials
Advanced Excel Essentials
Jordan Goldmeier
Excel often gets unfair criticism from data practitioners, many of us will remember a time when Excel was looked down upon—why would anyone use Excel when we have powerful tools like Python, R, SQL, or BI tools? However, like it or not, Excel is here to stay, and there’s a meme, bordering on reality, that Excel is carrying a large chunk of the world’s GDP. But when it really comes down to it, can you do data science in Excel?
Jordan Goldmeier is an entrepreneur, a consultant, a best-selling author of four books on data, and a digital nomad. He started his career as a data scientist in the defense industry for Booz Allen Hamilton and The Perduco Group, before moving into consultancy with EY, and then teaching people how to use data at Excel TV, Wake Forest University, and now Anarchy Data. He also has a newsletter called The Money Making Machine, and he's on a mission to create 100 entrepreneurs.
In the episode, Adel and Jordan explore excel in data science, excel’s popularity, use cases for Excel in data science, the impact of GenAI on Excel, Power Query and data transformation, advanced Excel features, Excel for prototyping and generating buy-in, the limitations of Excel and what other tools might emerge in its place, and much more.
DataFramed 
