What make alteryx become so useful for data analysis ? How would you compare alteryx to the other similar tool such as Tableau, Microsoft Power Query, Python?
Tableau -> Data Visualization
Python -> Data wrangling & Analytics
Microsoft Power Query -> ETL
If you want to compare Alteryx on an apple to apple basis, a fair comparison would be with Microsoft Power Query in your tool list. Alteryx is much faster, easier to use, and less restrictions on data sizes before your PC crashes due to extensive lag.
If you compare it with Python, Alteryx wins in some aspects of data wrangling in speed and ease of use. But Python triumphs in doing certain things such as XGBoost, SHAP Analysis, advanced analytics, etc. Of course... why compare when you can use the Python tool in Alteryx itself. The best of both worlds. Prep your data easily with Alteryx and ingest into Python too for complex models and bam, instant success.
Tableau is part of the SALT stack. Snowflake, Alteryx, Tableau. Storage, ETL, more ETL, Viz in that order. It's not directly comparable, more so a complement and necessary add-on if you want to visualize your data. Of course, you can look at PowerBI and Qlik too, but for Qlik... they just recently got Talend so not sure if that's still best practice.
In any case, Alteryx is a solid tool. It's the swiss knife of data analytics I would say.
Hello,
As someone who struggles with technology, what tips or tricks can you give that will help with learning Alteryx a little easier?
