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This is my first message to the community and I wish it will not be the last. Let me tell my case and I need your valuable suggestions.
I'm working in a Telecom company and using Tableau for dashboards to deliver executives requests. Most likely the requests come last minute with very high priority as usual. I do not have Python or similar coding knowledge, however, I started to study Python to pass my MBA BIA class, also helps with my daily work.
My department has multiple developers/coders who they use data manipulation/massage the data with Python. I'm using the trial version of Alteryx Desktop with the Spatial license that we are planning to buy and to use with Alteryx server. My manager last week brought this to the table, a discussion with other co-workers about whether we really need Alteryx or not. Most likely I will be the only person who will use it. The discussion was about Alteryx will be a solution to our daily needs that Python cannot do it. As you imagine all others were defending Python as it's free vs license cost of Alteryx. And to suggest it is better for me to learn Python.
I agree with them to some degree, however, with Alteryx all data process is easier and faster. They say there is nothing they cannot do with Python and Alteryx is not necessary and costly. I don't have enough arguments to defend Alteryx at that time.
So, all like as Alteryx professional, can you please share your experiences and observations with suggestions?
I've found myself in this argument before. How you win them over depends greatly in the environment you work in.
What has worked for me in the past is:
1. Take an example of something very complex done in Python and see how long it took everyone to learn that/how long it takes them to do currently.
Replicate that activity in Alteryx and show the time savings.
2. Friendly office challenge to see who can solve a particular use case, given the tool of their choice, the fastest.
In general you can do almost anything with any tool.
The difference is: time to learn the tool, time to complete the task, ease of replication, ability to only use one tool for the task. Being that Alteryx has the most diverse set of functionality with the easiest to learn interface, you should be able to show the most value in time savings.
I agree 100% with @patrick_mcauliffe, these are some great ways to approach the subject and get people to come around. I come from a development background, and still prefer using Python for many tasks. The beauty of Alteryx is that it doesn't need to just replace these tools, but can synergize with them. You can use Alteryx for things like data cleaning, especially with spatial data, before passing the ready data frame to a Python script for analysis. While its true that they can do the same things in Python, another major benefit of Alteryx is the how reproducible your results are once you've performed an operation. Coming from a Data Science background, there are often many steps necessary to get your data to a usable format, and sometimes you'll want a copy of your data stream at different points in this process, such as when performing feature engineering and looking to create benchmarks for your models.
My point is, I think the winning play is to highlight the ways that these tools work together, and as Patrick mentioned, try to show your coworkers some of the time savings they can have from performing certain steps with Alteryx rather than Python.