Microsoft 365 Copilot in Excel vs. Chat GPT 4: Implications for Data Analysts

As we navigate through the evolving landscape of AI and automation tools, the recent introduction of Microsoft 365 Copilot has sparked a mix of excitement and curiosity, especially for those of us entrenched in the world of data analysis. My firsthand experience with Copilot, particularly in Excel, offers a glimpse into its current capabilities and potential for future development.

Firstly, diving into Microsoft Teams with Copilot was a revelation. The tool's knack for distilling lengthy discussions into concise, actionable insights underscored its value for enhancing efficiency. However, the crux of my exploration centred around its performance in Excel, aiming to assess how it measures up to the advanced analytical capabilities of Chat GPT 4.

It quickly became apparent that comparing Copilot in its "Preview" stage to Chat GPT 4 was not a straightforward or fair matchup. Copilot's functionality in Excel is currently tailored to small datasets, with capabilities extending to sorting, filtering, elementary pivot charting and basic insights.

My planned approach was to test Copilot with a range of datasets, starting with a manageable UK Government open dataset before progressing to a larger, more challenging Kaggle dataset. While Copilot could handle basic insights and charting on the smaller dataset with around 300 rows, it failed with the larger dataset, faltering on even simple queries.

Switching gears to Chat GPT 4 revealed a stark contrast in handling the larger dataset. The data was a 200MB file containing details of 41,000 data-focused US job listings. Chat GPT 4 excelled across a variety of tasks, from detailed data analysis and visualization to the creation of an optimization engine for job seekers. This engine, which provided recommendations based on skills and expected salary impact, showcased the advanced capabilities of Chat GPT 4.

Now, let's talk numbers - specifically, the impact of the top three most listed skills of SQL, Excel, and Python - on salary:

- SQL: Carries an average salary increase of 0.2%. It's a staple in the data world, essential but expected.

- Excel: Is linked with an average salary decrease of 11%. It seems associated with simpler, less lucrative tasks and may not significantly enhance one's marketability unless paired with more advanced analytical skills.

- Python: Stands out with an average salary boost of 12%. This highlights Python's critical role in advancing one's career in data analysis.

Chat GPT 4's advanced data analytics capabilities were only launched through Code Interpreter in July 2023. With Python integrated into Excel in September 2023, I anticipate a rapid transformation in the tool's data analytics capabilities. This evolution may suggest a shift towards more complex data analysis, further altering the demand for traditional Excel-based analysis skills.

For data analysts, especially those with a focus on Excel, the message is clear: the advent of tools like Microsoft 365 Copilot signals a time of change, not obsolescence. Upgrading skills, particularly in Python, appears to be a strategic move to stay relevant and competitive in the dynamic field of data analytics.