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You might want to (or need to) collect, store and process unstructured text items with associated metadata. Examples could be to set up a library for research purposes or to build a tool to watch the public discourse for relevant conversation pieces. This guide will showcase a just-the-basics approach to build one possible implementation of such a tool in Alteryx.
Having in-depth demographic information is often seen as the holy grail in the eyes of data analysts and their business stakeholders, and there is a good reason why: the context that can be added to your analytics, as a result, is hugely advantageous.
We want Designer to look like a powerful modern tool that gives you actionable results. When you show people workflows you've developed, they should see the same powerful tool you do, even if they've never used Designer.
Ever wonder what an Alteryx C++ developer's favorite code editor is? Or a Python developer's favorite book? Or how about a front-end developer's favorite testing framework? If you answered yes to any of those questions, or just wonder where this is all going, continue reading!
As we develop workflows, it is inevitable that we will need to make additional modifications downstream of our data. To see the updates, we need to run the workflow. Depending on the data, this can take a long time. Let’s be honest, even waiting a couple of minutes to re-run the workflow is too much time... Ain't nobody got time for that.
I've learned a lot about computers, business, and collaboration through visiting the grocery store. Read about one of my trips here: The Grocery Store is a Fascinating Place. What more can be learned from a trip to the grocery store? How about Data Science!
Have you ever wondered how new tools placed on the canvas know what fields are being passed to it? Are they psychic or something? Not at all! It's metadata! The metadata fields Name, Type, Size, Source, and Description are all passed from tool to tool before you even run the workflow. When working with the Python SDK, you are in charge of building and passing that information to downstream tools. This blog post will explain what that entails and how to implement it in your Python-driven plugin.
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.
Have you ever wanted to be notified if a workflow ran into an issue? Or get push notifications when incoming data quality didn't meet your standards? Check out the Twilio SMS Alert tool, which will send you a text message based on the tool's incoming data.
No one likes to see an error message, but as an Alteryx tool developer, you have the ability to make seeing an error a useful experience that helps guide the user through configuring your tool. This article will show you how to add error messages through the macro back-end or the front-end.
Under more pressure than a Neutron star? Trying for Overachiever of the week? Now you can use Designer 2018.2 to publish metainfo with a Tableau Hyper file! You also have more time to work on being an overachiever because this connector remembers Tableau Server connections for you. Kind of like how the calendar in my phone never forgets birthdays (never ever - even birthdays I no longer need to remember, like all my exes), only the Publish to Tableau Server tool is way less annoying. A few things you should know about this all new connector...