Alter.Nation
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Looking back, I wish I would have had known about Alteryx for my whole career! It would have been so helpful automating, simplifying, and expediting analytics and reporting.
I started my career learning Cognos, and simple data reporting and automation. I didn’t get to learn how to query my own data, but I did learn the importance of looking at all data. I then got the chance to join a major retailer, Wal-Mart, and learn about analytics in several different areas including finance, HR, and partnering with other areas of the business while in finance. It was at Wal-Mart I got introduced to the one platform to rule them all: ALTERYX!! (Yes, I love LOTR!)
While at Wal-Mart, I also got to partner and see analytics from a fraud perspective, customer segmentation perspective, and merchandising. I learned about data structure, querying my own data, and the importance of understanding data manipulation and cleansing. Now at Whole Foods Market, I get the opportunity to be a leader in data and analytics helping set strategy for different aspects within the analytics space, including best practices for data handling, Alteryx usage, Alteryx server setup, data governance, analytics governance, and numerous training topics.
Knowing all the skills I have now, the most important skills I wish I would have focused on earlier include:
1) Data Literacy
2) Effective Communication of Results
3) Analytics Process Automation
Probably the most important skill that I feel analysts need to know to be successful in an analytics career is data literacy. Gartner has a great article on data literacy that can be found here. Specifically, at that link, they talk about being able to read, write, and communicate data. This tells us data literacy also deals with the effective communication of the results. The effective communication of the data with context can be a struggle for many analysts especially early on in their career due to lack of experience in doing so.
Alteryx helped me learn a lot about data literacy quickly. The transparency in the way it handles data could show me how to not duplicate data in joins, what it means to filter something out, what would happen when I cleanse my data, and what that does to calculations, among many other things. The one aspect it also helped with was gathering business knowledge on the front end of the problem. Knowing how to handle data in a process, specifically in building Alteryx assets (workflows, macros, apps) I learned that asking “why” is a great tool in an analyst tool belt. Getting the requirements to build an automation of process or analytic process allows you to understand why that arm of the business does certain things. Maybe some of the data under a certain tag is testing data or they are only interested in hourly associates and a certain tag in the data is for salaried management. These pieces of information allow you to gain insight into what is important to that business and focus the results to analyze the important points in the work.
Example of data transparency:
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One of the challenges for many analysts early in their career is the balance between getting everything done (sometimes in a manual manner) and automating a process fully so self-service analytics can be achieved for business partners. This is simplified by Alteryx. No more dealing with Excel formulas and pivots and having to remember the order in which you did things. Alteryx has easy documentation and allows you to decide the level of automation you put into something. You could do several standard inputs or a dynamic input to read in all files at once like so:
You can even go as far as turning a workflow into an Alteryx analytic app and empower the end-user with self-service analytics. This is where I currently have a lot of focus. We have a lot of questions come our way and the best way to help with these is to allow users to simplify their processes, simplify getting to their data, or simplify simple analytics or reporting.
The above pictures are an app I built that allows individuals to essentially build their own sales pulls without writing a single drop of code. All they do is navigate the interface and make their selections as they need. We are even looking into adding a portion that would do some forecasting on the sales and would give the option on the level of granularity of the forecast. This could fully automate and standardize how different areas of the business could forecast and work through different things to anticipate.
Overall, in the last 5 years, Alteryx has taken me from data novice to data guru and on top of that, I have learned so much in the ways of automation. Along my journey, I have learned more R code, Python, command line, and HTML all in the ways of learning how to automate even more. Alteryx introduced me to the idea of turning business problems into puzzles to solve and that has been a blast! It continues to impress me each day I use it, and even after 5 years of use I keep learning something each day! If only I had used it my entire 8-year career, who knows what I could be doing now!
