Many professionals are shifting away from traditional tools like Excel and Google Sheets for handling CSV files, opting instead for more powerful solutions like DuckDB combined with SQL. One user shares their personal experience of transitioning from using Excel's pivot tables to executing SQL queries to extract unique user IDs directly from CSV files. This new method not only simplifies the process but also allows for seamless data exporting back to CSV, eliminating the hassle associated with spreadsheet software. The advantages of DuckDB are highlighted through various user insights, illustrating how SQL can often be more intuitive than complex spreadsheet formulas. Users appreciate features such as applying SQL joins and window functions directly on CSV files, which enhances the convenience of ad-hoc data analysis. Additional functionalities include reading files from various sources, including URLs and cloud storage like S3, further streamlining workflows. Some users also mention alternative tools and extensions that complement DuckDB, reflecting a growing interest in open-source solutions that enhance data manipulation capabilities. A sense of community is evident as users share their favorite life hacks for working with CSVs and DuckDB, from using parquet files to running queries that reveal data structure. The conversations reveal a collective recognition that SQL serves as a backbone for efficient data analysis, making tasks faster and smoother. Overall, the shift towards these modern data tools signifies a broader trend in data management, where traditional spreadsheet applications are being replaced by more robust and flexible alternatives.