DataFramed

#228 Are Spreadsheets Still Relevant For Data Analysis? with Jordan Goldmeier, Author of Data Smart

Jul 22, 2024

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.

35:21

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Episode guests

Jordan Goldmeier

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Quick takeaways

Excel remains relevant in data science for algorithm creation and communication with stakeholders.

Power Query in Excel simplifies data transformation and analysis, potentially integrating generative AI in the future.

Deep dives

Excel's Role in Data Science

Excel is discussed as a potent tool for data science despite facing criticism from practitioners favoring Python, R, or SQL. The episode features insights from data visualization expert Jordan Goldmeyer, who asserts Excel's continued relevance. The visual and formulaic nature of Excel assists in algorithm creation, data visualization, and communication with non-technical stakeholders.

The Enduring Relevance of Excel for Data Analysis

02:11

Intro

2min

The Evolving Role of Excel in Data Science

9min

Empowering Data Analysis with Power Query and Excel

12min

The Mindset of Data Professionals

4min

The Importance of Clear Communication in Data Analysis

3min

Fostering a Data-Driven Mindset and Transitioning Beyond Excel

4min

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.

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DataFramed

#228 Are Spreadsheets Still Relevant For Data Analysis? with Jordan Goldmeier, Author of Data Smart

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

Deep dives

Excel's Role in Data Science

AI Impact on Excel

Power Query and Data Transformation in Excel

Cultivating a Data Mindset

The Enduring Relevance of Excel for Data Analysis

Remember Everything You Learn from Podcasts