This is the third time in about 6 weeks that I’ve needed to create a rank in Alteryx and couldn’t remember how. Each time I had to dig through projects to find what I did last time. That means it’s time to write it up so I can find it next time. Read more to learn an easy way to create a rank in Alteryx.
Alteryx is data wrangling software commonly deployed with other applications like Spotfire and Tableau. This category will contain articles on Alteryx best practices, tips, tricks, and learnings. I am a new Alteryx user and will post as my skills develop.
One of the things I love about Alteryx is how fast it pushes data through a workflow. However, sometimes, we need to run one part of a workflow before another. In other words, we want to control the order of operations in Alteryx. I knew the application could do this, but to incorporate it into my workflow, I had to learn a few new tools. Read on to learn which tools allow you to control the order of operations in a workflow.
The more I learn about Alteryx, the more I love it as a tool for data wrangling. I recently had 2 use cases pop up where I needed to be able to dynamically change the data being queried. I knew the application could perform this task, but I hadn’t yet learned how to create a dynamic query in Alteryx. Now that I know how I’m writing it up for future reference and other people to use. Two use cases are presented because they are configured differently. Read on to learn how.
It’s a fact. If you have manual data entry, there will be errors. I found this out the hard way when working with our completions team on a Spotfire KPI project. We built the Spotfire KPIs and were attempting to tie out to spreadsheets. The numbers didn’t match. Discrepancies consistently traced back to bad data entry. We would fix the bad data, but without proper controls to keep it out, we were chasing our tails. So, we addressed bad data with a QAQC or error report. The first version was all Spotfire, but it had flaws. Version 2 performed error reporting with Alteryx. Ultimately, I wound up with a combination of Alteryx and Spotfire. To see what it looks like and how it was implemented, read on.
I haven’t written very much about Alteryx, although I do now use it EVERY SINGLE DAY. I’ve been hesitant because the Alt Nation Community is fabulous. I struggle with the utility of publishing my own content when it’s not likely to register in search results. However, I frequently write just for myself. And, it pays off. This week I referred back to a Spotfire post I wrote over 2 years ago. Therefore, I’m writing about a problem I ran into this week with scheduling an Alteryx workflow to run on the last business day of the month. If this is a problem you’ve run into, read on.
I’ve never found a great way to explain what I do. Analogies help right? The first analogous thing that pops into my head is a Rubix cube. My day to day work feels like trying to solve a Rubix cube over and over, and the cube is a big pile of dirty, messy data. Thus, much of my day to day is troubleshooting data wrangling problems.
Some days, it’s incredibly satisfying, as solving a Rubix cube is. Other days, I want to rip the stickers off and throw it out the window. When I drafted this post, I was in “rip the stickers off” mode. I was frustrated with how long it took to solve data wrangling problems. When I get in that mindset, I want to share what I learn so other people don’t suffer as much. Thus, this post discusses my top 5 ways to approach troubleshooting data problems. These methods will apply no matter what application you are working in or if the problem is related to data wrangling or logic problems. Read on for details.
As regular readers know, I attended the Gartner Analytics Conference in Orlando a few weeks ago. Since then, I’ve been synthesizing my key takeaways in blog posts. My first key takeaway centered around Organizing the Chaos. Last week, I followed that up with a post on Governing Self Service BI. This week, I am writing up the last key take away — drive analytics innovation with efficiency.
One of the most common problems I run into in while building Spotfire projects is requests that are too large. They begin simply with a request for data or a modification to an existing project. However, it quickly balloons into more and more until we’ve created a monstrously huge project. One of these monsters jumped on my desk last August, and I’ve been working on it since then with a few stops and starts. Last night, I wrapped up a week of work in Midland. I was about to shut down my machine when I realized I wanted to write up what I’ve learned about how to increase the speed of delivery in these monster project situations.