Data Engineering Tools vs Spreadsheet Tools
Developers should learn and use data engineering tools when working on big data projects, building data warehouses or lakes, or implementing ETL/ELT processes for data-driven applications meets developers should learn spreadsheet tools for tasks like data preprocessing, quick prototyping of algorithms, and generating reports, especially in data analysis, business intelligence, or when collaborating with non-technical stakeholders. Here's our take.
Data Engineering Tools
Developers should learn and use data engineering tools when working on big data projects, building data warehouses or lakes, or implementing ETL/ELT processes for data-driven applications
Data Engineering Tools
Nice PickDevelopers should learn and use data engineering tools when working on big data projects, building data warehouses or lakes, or implementing ETL/ELT processes for data-driven applications
Pros
- +They are essential for roles in data engineering, analytics engineering, and backend systems that require handling high-volume data streams, ensuring data quality, and automating data workflows
- +Related to: apache-spark, apache-airflow
Cons
- -Specific tradeoffs depend on your use case
Spreadsheet Tools
Developers should learn spreadsheet tools for tasks like data preprocessing, quick prototyping of algorithms, and generating reports, especially in data analysis, business intelligence, or when collaborating with non-technical stakeholders
Pros
- +They are essential for handling small to medium datasets, automating repetitive tasks with macros or scripts, and integrating with other tools via APIs or exports
- +Related to: data-analysis, formulas
Cons
- -Specific tradeoffs depend on your use case
The Verdict
Use Data Engineering Tools if: You want they are essential for roles in data engineering, analytics engineering, and backend systems that require handling high-volume data streams, ensuring data quality, and automating data workflows and can live with specific tradeoffs depend on your use case.
Use Spreadsheet Tools if: You prioritize they are essential for handling small to medium datasets, automating repetitive tasks with macros or scripts, and integrating with other tools via apis or exports over what Data Engineering Tools offers.
Developers should learn and use data engineering tools when working on big data projects, building data warehouses or lakes, or implementing ETL/ELT processes for data-driven applications
Disagree with our pick? nice@nicepick.dev