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The traditional approach to data access and preparation is often time-consuming for data analysts in the line-of-business. Relying on IT and SQL developers can often can be so frustrating that you’ve taken matters into your own hands and learned how to write SQL yourself. One of the biggest struggles analysts face in writing SQL is just getting it to work! There's no autocorrect in SQL, so an incorrectly placed period or comma won’t be caught automatically — and can make your entire script fail.
Alteryx takes a different approach with a workflow-based environment that allows you to prep, blend and analyze data from multiple data sources, including unstructured data. Instead of spending your time testing and debugging code, you construct a repeatable workflow that visually shows colleagues across the business – other analysts, IT, and business decision makers – exactly how you extracted and transformed the data. The result? Less time spent writing code, transparency, and more consistency.
We've listed some of the most common data-related processes that many analysts code in SQL, and alongside them show how you would do the same process using Alteryx. These examples are meant to help analysts who write SQL code to understand how to translate their SQL knowledge into an Alteryx workflow.