This article is by Ian W and originally appeared on the Alteryx Data Science Blog here: https://community.alteryx.com/t5/Engine-Works-Blog/Evaluating-Designer-For-Your-Workflow/ba-p/404460
It’s no secret that Designer users are also Designer fans. These folks wander the halls of their respective organizations rummaging for problems they can solve using Alteryx. Ok, maybe that isn’t totally accurate, but many successful Designer users are sought out by other departments to solve the problems they can’t solve themselves. Success gets noticed and most Designer users crush expectations. For those users, a paradigm shift occurs; problems are no longer impossible obstacles to be avoided if you know what’s good for you. Instead, they become puzzles that haven’t been solved yet… It isn’t extra work, it’s more success waiting to be unpacked.
At this point, users become the raving fans who can’t imagine their jobs without Designer. It’s impossible not to see opportunities to leverage Designer to solve a plethora of business problems. Lunch with colleagues, standing by the coffee pot, and sitting in on meetings provides a steady stream of use cases screaming out “SOLVE ME.” Unfortunately, some of those problems require intimate knowledge of the subject matter and all of those problems require time. Time which has already been allocated elsewhere. But it would be wrong not to share that there is a better way. “You should check out Designer…”
That’s where this article come in. It can be difficult to understand why you’d want to use Alteryx and get a handle on what you’ll need to do to become a successful Alteryx user. If you are new to Alteryx, you will find that Designer is able to alter your data in powerful new ways, but you will also find that it alters the way you think about and interact with your data. Alteryx can help you to recoup countless hours of your time and free you up to work on more challenging problems, but those gains come from a change in the way you interact with your data. Change is difficult and can be frustrating at first, but below you’ll find a brief summary of what you can expect and the benefits you’ll enjoy as a result of your efforts.
The Benefits: Let’s start with what you get out of this… When you use Alteryx, you:
- Gain the ability to work on multiple items at the same time. Instead of going to each data source and making the same edits, you can pull them all in at once and run them through the exact same workflow.
- Reduce the manual copy and paste work, the computer freezes, and human errors. Instead of hitting row limits and wearing out your “Ctrl”, “C”, & “V” keys, use a tool that was created for the modern dataset.
- Increase the frequency and repeatability of solving problems. When it doesn’t take you hours of manual effort to prepare your datasets for analysis, you can update your dataset as often as you like. Your answers won’t go stale while you are trying to find them.
But with great power comes, a learning curve?
Interaction with your Data: The first difference you’ll notice when using Alteryx, is that you interact with data differently. If you are coming from spreadsheets, you are used to being able to navigate to your sheet, open it, make edits, and save. In Alteryx, you’ll still navigate to your data source(s), but you won’t open them per se. Instead, you input them and create a workflow, which will perform the “editing” you used to do manually. Instead of hitting save, you’ll use output tools to write your results to a new location or overwrite the original source. This method reduces the dependency on you, the user, to make all edits which reduces the chance of error. It also makes repeating the workflow as simple as clicking run or scheduling regular iterations.
Framing your Issues: It’s easy to take things that come naturally for granted. There is nothing wrong with being comfortable, but when you can’t use the familiar, those things you took for granted are very noticeable. When using Alteryx, you will find that the way you’ve been thinking about and solving problems is not effective even though you’ve always used that method. Your first instinct may be to try dragging cells and color coding your information, but those actions require you to see every item that gets processed. By clearly stating what you need from the data and writing detailed instructions, you allow the computer to do the “heavy lifting.” There will be a learning curve as you find those things you’ve been taking for granted, but in the end you will be able to work with more data than was possible with your old way and you’ll do it in less time.
Solving in Robust Terms: Finally, think about all the steps you take when cleaning and preparing your data. Then think about all the calculations and formatting you do. All those steps need to be added to your workflow and configured to ensure it is appropriate for your dataset and will produce the results you desire. This will take practice since you won’t be able to just grab the 10 values you are interested in as you have in the past. Instead you are creating detailed instructions about how to isolate and prepare the data you need in a repeatable manner, regardless of whether your dataset changes.