Product Guides
The Alteryx Guide
For SQL Users
The traditional approach to data access and preparation can be time-consuming for data analysts. Some frustrated analysts take matters into their own hands and learn to write SQL rather than rely on IT and SQL developers. 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 sources, including unstructured data. Instead of spending your time testing and debugging code, you construct a repeatable workflow that 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, greater transparency, and more consistency.
We’ve listed some of the most common data-related processes that many analysts code in SQL. Alongside, we show how you could do the same using Alteryx. These examples are meant to help analysts who write SQL code understand how to translate their SQL knowledge into an Alteryx workflow.
To learn more about how Alteryx can empower SQL coders, download the whitepaper Enabling Self-Service Data Analytics: 5 Ways Alteryx Helps SQL Users. Then try it for yourself, with a free Alteryx 14-day trial.
Select
SELECT, FROM, WHERE, GROUP BY, HAVING, ORDER BY
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Alteryx |
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This is the full Alteryx workflow for the SQL SELECT statement. |
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Cross Join
Cross Join
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Alteryx |
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![]() This Alteryx workflow appends Distribution Center records to each Customer record. |
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Where Between
Where Between
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Alteryx |
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![]() This Alteryx workflow filters Customer Order data specifically for orders placed between Dec 1 – 31, 2016. |
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Where In
Where In
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Alteryx |
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This Alteryx workflow filters for the customers whose country is either the United States or the United Kingdom. |
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Distinct
Distinct
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Alteryx |
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![]() With the Unique tool, this Alteryx workflow separates the data into two streams (duplicate and unique records), based on the fields you choose such as, in this example, country. |
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