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Some finance processes in the tax world require you to monitor the balance of various accounts over time. The problem is, just like your personal bank account there isn’t always a change in balance every day. Meaning if you were to plot this data on a graph there would be gaps in the information for which there was no change. The way to solve this in Alteryx comes in two steps, first we need to identify exactly what dates are missing data and create rows for them in our dataset. Then we need to run calculations on this data to determine what the balance should be on the days that had no change.
As an experienced Alteryx user, it can be easy to forget that there is a learning curve for many folks just starting out. This article takes a look at a new Designer Cheat Sheet which was created to help new users get started.
If you google (a verb) "Date Frustration," the 7th article is Date Conversion Frustration - Alteryx Community. As a follow-up to my previous blog post, Marquee Crew's Guide to Dates, I'll provide you with some tools to better handle incoming date fields and help to teach you how to convert strings to dates. Even with tools like the DATETIME macro, this can be challenging. Hopefully, you'll avoid the frustration and skip directly to happily ever after.
Recently we celebrated the launch of our long anticipated Tool Mastery Series, a collective of Knowledge Base articles tasked with communicating the most inspired uses of each Alteryx tool. Check out how we automated all the hard parts and brought the series to life!
For the love of formulas; why would you take the time to configure many formulas and risk errors in the process when you can rely on a known set of formulas and dynamically create tens, hundreds or thousands of variables with little to no effort?
Larger workflows sometimes require a little extra effort to navigate around. We are exploring some enhancements to make it easier to move across a large canvas and we would love to hear your thoughts, suggestions, and concerns.
Developing resource-intensive workflows can be a challenge when testing changes involves running the workflow through iterations that may take several minutes or more before being able to see results. This post walks through using the Cache Dataset macro to develop workflows in a smarter way, avoid repeated long run times, and speed up the process of blending and analyzing larger sets of data.