What I like about Alteryx is that it uses a node based system kind of like KNIMe but more sophisticated. It also allows for us to utilize our own code which a huge benefit for the work that has already been carried out. The most useful aspect for us is the ability to aggregate data from different sources. Orcale, Teradata, SQL Server, large datasets are able to be generated easily and quickly. Sometimes when trying to create datasets when SQL Assistant is lagging or not running at peak performance, I switch to Alteryx and am able to generate my datasets. It is a really good tool for varying levels of data analysis experience.

There is not a much to dislike about Alteryx. Perhaps those individuals with very basic and beginner levels of data analysis and data literacy make require more training to use it effectively. Some of the syntax in formulas are different from other coding languages and require some troubleshooting.

The biggest problem that Alteryx solves for me is the ability to aggregate data from different servers and sources into one data set with all required fields for necessary data exploration and analysis.

I have been using Alteryx for 6 months now. It helped me automate my Risk Audit tasks that took almost 2 months to complete.

My best moment came when a manager called me with a question. Answering it would take data from two or three databases and munging in MS Excel.I figured it would take about 3 hours.

But wait, I had received a license for Alteryx, so I installed and launched it. Input Data tool, connects to databases and I can write my own SQL? Henceforth, I can join data from different databases with the eponymously named Join tool. A few tools later, Filter, Formula, Summarize, and I was done.

Alteryx is very easy when you focus on the applying part. If you lack knowledge in SQL or Python then it can be hard to understand.

You need to write SQL query to bring in the data before manipulation.

As soon as you bring an input on the canvas, wrap it in a container. Using "cache and run workflow" is the best. You can't cache multiple sources at once, so you want to disable all containers but 1, cache that one. Then enable the next container, cache, etc.

Learn to leverage the in-db tools. When first prototyping, my "input in-db" will pretty much always be select * from table, and second tool will be "select in-db". This allows you to sort / rename the columns and see everything on the table without having to go into the metadata window. I go back and optimize later.

• If I am doing large data pulls, I will typically chunk out what may typically be a query. For instance if I am joining a customer table (let's say 100 rows x 15 columns), to the fact table (100,000 rows x 5 columns). Those 2 smaller sources coming through the pipe run a lot faster than if you were to stick them together with SQL (in this example 100,000 rows x 20 columns).

The best part of using Alteryx is having vast support information available online. As someone who often learns by doing, the Alteryx online community has played a significant role in my learning how to use the software best.

My one dislike is the random moments when my workflow will experience an issue caused by a bug. This happens when dealing with complex workflows and resolves automatically.

I use Alteryx to deal with creating solutions involving complex data. This can range from creating workflows to process large amounts of blockchain data to prepare individual tax returns to other process-focused solutions involving extensive data.

What I like most about Alteryx is that I am able to organize a workflow to form how I think. Because of that, I am able to work at my optimum. I can also add comments, tool boxes for organization, and colors. These additions can help to walk a different user through my workflow like a story.

The toughest thing about Alteryx is probably it's best feature. Because it is so expansive, there is a lot to learn. However, the academy and user discussion portal are best-in-class. Even in designer you can type a question that links to the user discussion portal.

It helps our organization pull data, organize data within our folders, clean and prep data, load data into lakes and warehouses. We also find exceptions to our reporting, create automated reports for regulatory reporting. We have used it to map our customers to branch locations, predict best approaches for customer contact. We parse text and pdf files to remove automation hurdles for accounting as well.