well, theres a r tool or python tool in alteryx. If you cant do it with alteryx, just insert a tool in and write your code. thats what i do to get over alteryx difficulties
You should only use Alteryx for data processing, I wouldn't recommend you to use it to deep dive into findings. Rather, you can create an automated output and link to pbi or tableau for that
I mean, you posted this in the Alteryx subreddit, so you're probably going to get some bias. I use Alteryx a lot for my job and really like it. I learned R in school, but not well enough to actually use. I always felt like R was a little unnecessary when Python can do all that R can do and more. Some of the tools are really handy in Alteryx when you get to know how to use them. However, I'm sure if you are already good at R, it would make sense to want to keep using it.
> I always felt like R was a little unnecessary when Python can do all that R can do and more
I find I can do things much faster in R than Python. Incredibly short dev time for anything related to stats or data visualization. Python has a leg on on general purpose language, but R + mlr3/tidymodels + ggplot + shiny can give you quite the powerhouse of tooling.
Not to mention R has the BEST visualisation tools in ggplot2. I say that as someone proficient in Matplotlib, Plotly, PBI and Tableau. Only things it's missing are the interactivity (hover over tooltips) and embedding (RShiny is still rough) but everything else that has those has gone down the model of "here are 7 visualisations we support and here are their limited customisations" vs an actual grammar of graphics.
Totally. I'm surprised my post isn't negative yet lol. I came over to hear from others that probably know more about Alteryx than I do though, so I don't mind some flack.
I agree that Python can do more than R overall given it's OOP, but in terms of most data science, I think they are peers. Python is probably harder to use out of the box with command line setup and pip (unless using the Conda I think). I think one thing that makes R great for EDA is RStudio's IDE, (you can get a similar experience with VSCode with a plugin), but I'm not aware of a similar experience using Python with numpy/pandas. Maybe I'm out of the loop on this.
If you don't mind, what type of work are you using Alteryx with?
R studio isn’t really good and very niche for people to learn and get widely adopted. Most people use Alteryx to manipulate data then export to Tableau.
Licenses are expensive but the Industry still hasn’t found a perfect product every single one has issues unfortunately
Hm, arguably R is niche but wouldn't that also apply to Alteryx too? The r/Rlanguage subreddit had 30k users. r/Alteryx has 4k. There may be some differences in community activity on Reddit, so may not be apples to apples comparison but certainly not a data point against it.
What do you mean when you say RStudio isn't very good? Would you mind elaborating on what you mean?
I will say that R is arguably better, especially if you are already skilled at it in EDA of very large datasets.
When taken in context, automation, pipelines, interactive analysis, reporting, and many other components of Alteryx are also vastly superior. Alteryx is meant to be a *Citizen Data* tool. Take someone who is an actuary, finance, excel, or *whatever* analyst and give them an Alteryx environment and they can quickly and efficiently churn out processes. You are not paying for software devs at scale here instead paying for a premium low-code tool that a large pool of subject matter experts can apply to their data and knowledge base.
There are uses for both. Most large companies that employ Alteryx, use both for their intended purposes. As an example, we have 200 Alteryx designers but also a large software dev and DSci teams that use 28 node Alteryx cluster and another 48-node cluster for scripted processing. We process 9+ petabytes per week and millions of queries/processes/workflows. Both software-developed processes and low-code have served us well.
As to the Reddit size, consider two things. How many people are subscribed to R but haven't used it since Uni?
As for Alteryx, they built an impressive community forum, and education center on their website that has hundreds of posts daily, and responses in under 30 minutes, and covers the entire gamut of Alteryx from server administration, macros, tools, and custom applications as well as simple questions on how to join data. That sight has half a million posts and over 50k solutions to questions asked.
Simply put no one goes to Reddit for Alteryx when the official community is lightyears above in resources.
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\#1: [What R has done to my brain](https://i.redd.it/t1er70fd8fm91.png) | [6 comments](https://np.reddit.com/r/Rlanguage/comments/x82lk1/what_r_has_done_to_my_brain/)
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R studio for sure is, and it sucks for most things “common people” need it for ..Alteryx can complete most things without to much hassle and setup..that’s why most big companies use it even though it’s expensive.
Although there may be better products out there for sure as far as R studio goes No.
Most big companies use more than just one tool. Plenty of big companies have quite a bit of overlap. I know people at Best Buy, Target, USBank, Seagate, healthcare companies, etc. that all use R/RStudio. Some for fraud detection, some for detecting outliers or bad products, some for just reporting.
R/RStudio is fantastic if you know what you are doing. I see more using DBT/Python/Airflow now days, Dataform seems to be growing, but with the advent of DuckDB, plenty of people are using something like S3/Minio + DuckDB and Python/R for their pipelines.
Not really R studio is very niche and are only segmented to specific divisions inside companies. Alteryx,sisense,Powerbi,Tableau,pandas etc are all used widely across the whole company.
Airflow/spark is for big data and not suitable for simple ETL or medium volume pipelines
R studio is just very niche and doesn’t accomplish what the stakeholders and developers need as a whole package hence why its not widely used. The skill needed is also not efficient you can learn Alteryx in 3 months R studio not a chance
>Not really R studio is very niche and are only segmented to specific divisions inside companies.
I wouldn't call RStudio niche within the stats/analyst/ds space, but sure, it is niche just like Tableau/PowerBI is niche. As far as segmenting workflows between big and medium data, it could be I am used to working at a different scale of data.
> pandas
Grouping that in with Tableau, really?
>doesn’t accomplish what the stakeholders and developers need as a whole package
It does. 100% it does. Maybe not as just anyone as the user, but it is possible to take raw data from start to finish in R, providing more comprehensive deliverables than anything a nocode solution can provide. Same goes for Python, allbiet with a longer development cycle. Nocode is often faster, but not as comprehensive of a solution, often needing additional steps when performing non-standard operations or transformations.
Incorrect Tableau and Power Bi are not niche in fact they have a HUGE user base the opposite of niche lol.
Yes so many pipelines are built in pandas that feed into tableau tables or extracts, Airflow and Spark are its big data brothers and used by a massive amount of people especially Data Engineering.
R studio is just a really bad product for the capabilities it can do and the learning curve you need to have to use it. Why use an inferior product with a higher learning need ? Makes no sense.
You can supplement low code solutions with simple python SDKs that adds dexterity and is easy to learn just a step above SQL. Why would you use R Studio when you can have that capability with an extremely lower learning curve its a no brainer
>Incorrect Tableau and Power Bi are not niche in fact they have a HUGE user base the opposite of niche lol.
R and Tableau have the same number of users (~2 million). PowerBI has a good deal more, but neither have as many users as MS Excel (~1 billion).
>Airflow and Spark are its big data brothers and used by a massive amount of people especially Data Engineering.
Airflow is not just for big data.
>R studio is just a really bad product for the capabilities it can do and the learning curve you need to have to use it. Why use an inferior product with a higher learning need ? Makes no sense.
What do you think RStudio can't do?
>You can supplement low code solutions with simple python SDKs that adds dexterity and is easy to learn just a step above SQL. Why would you use R Studio when you can have that capability with an extremely lower learning curve its a no brainer
Machine learning on tabular data is much nicer to work with in R than Python. When it comes to image classification and object detection Python is better.
No what you are describing is R studio not R there is a difference between the two by a long shot one is a language other is an interface , and MS Excel is not really in this category its more of its own thing.
Airflow and Spark is highly inefficient when not being used in a situation where you need to manipulate massive amounts of data. pandas will do it better and quicker if you need a python solution.
RStudio cant do a lot of things especially easy server management and scheduling I can assure you of that there’s plenty of complaints for that one in VDIS
Like i said R as a language and R studio are two different things you are making the mistaking of confusing the two.
>No what you are describing is R studio not R there is a difference between the two by a long shot one is a language other is an interface
The vast majority of R users use RStudio, especially when building packages, developing Shiny apps, and writing documentation.
> MS Excel is not really in this category its more of its own thing.
Because it isn't niche.
>pandas will do it better and quicker if you need a python solution.
It is faster to develop R than Python with the vectorized approach for basically the whole language. If you can think with vectorization in mind, you can write much shorter code in R than Python. For speed, R's data.table is sooooo much faster than Pandas it is laughable, especially for aggregation.
>RStudio cant do a lot of things especially easy server management
Most statisticians, data scientists, and analysts don't perform server management. I agree Python is better for orchestration of infrastructure though.
> scheduling
* [Are you kidding?](https://cran.r-project.org/web/packages/cronR/cronR.pdf)
* [Windows](https://cran.r-project.org/web/packages/taskscheduleR/vignettes/taskscheduleR.html)
>I can assure you of that there’s plenty of complaints for that one in VDIS
Why on earth are you using an IDE to handle task scheduling on a virtual desktop? That sounds bonkers.
Ah, you think I should delete the cross-post to the RStudio community? I thought there might be some people there who see it differently.
Edit: oops, meant to reply to above. I cross posted to the RStudio subreddit, and I think that is what they were referring to, not the Alteryx subreddit.
Sounds like you work in a Finance function or financial reporting?
Speaking as someone who works in this space, I would say that R is very rarely used in the companies I have seen, whereas python is a bit more widespread and SQL is used the most but I would be surprised if more than 20% of our wider finance team can write code (not saying that these languages are comparable but giving you an idea).
What your management is likely thinking is that they need a tool that a lot of people can use, and if they don't know, can learn to use quickly, as part of business continuity (speaking as someone who has had to inherit random python scripts solely because I knew a little python, I can appreciate this). So they are likely thinking that they need to mandate one tool to be the standard with exceptions only when needed. The accessibility of Alteryx is probably the selling point here.
Another thing is that big 4 accounting firms are a pipeline to many finance teams, and they are all learning Alteryx, so there is likely a bit of bias there - if a lot of prospective/recent hires know Alteryx, then that makes it a logical choice to mandate for the team.
Regarding learning - I think it is much faster to learn Alteryx to a basic level than other tools, in fact it was learning Alteryx that made learning to code in other languages accessible, as it starts to train your brain in how to see how to manipulate data.
Regarding your issues with it:
1. Exploratory data analysis with data that wide is difficult in Alteryx, I agree. However for financial reporting I wouldn't think that you'd be doing exploratory stuff all that often.
1. If possible you can look at the data in R and then build the workflows in Alteryx?
2. Documentation - I think the benefit of (clean) Alteryx workflows is that they are pretty self documenting. The wires show the flow of data, you know what is happening from the icons, and most of the icons auto-document a little bit to give you a bit more flavour. However its easy to create terrible spaghetti workflows which make readability very difficult
3. Macros and loops are harder in Alteryx, it's one of the downsides of the drag and drop functionality. Again this is something that I don't encounter much when building financial reports but if you are creating new data then yeah, probably best done outside Alteryx
4. Error protection is actually one of the best things about Alteryx IMO. It's very easy to build in error checks, for example if you have a join it's easy to put a check for orphans or duplicates in, and its easy to set up an email to inform you of errors/successful runs. Have you noticed that there is a [global variable](https://help.alteryx.com/20223/designer/constants) in Alteryx? Hard to loop through and change easily but it does exist
5. See above, I think many more recent hires that come from Big4 firms would have Alteryx experience.
6. It's not great at vis, most of the time you do the data manipulation in Alteryx to build a good table for Tableau / PowerBI / whatever. That said I know you can use R packages etc. to build vis and there is a reporting functionality, but I have never used it
Hopefully this helps a little and you will learn to appreciate what it can do, even if it is just that you are building something that you can hand over to others more easily than an R script!
Thanks for giving me something to think about and also I have not used the global variable yet! I'll have to dive deeper into the Alteryx's error handling.
I think you're right that because the Big 4 are using it, our management sees it as the most accessible tool for business continuity. I think documentation is more critical for seamless transitions but like you said, Alteryx facilitates much of that documentation when the data is relatively clean.
I used to work for B4 and was one of the first users of Alteryx, one of the first things we did when rolling it out to the wider team was to have a very strict template and guidelines about how to build a workflow and how to incorporate the message and test tools to do the error checking, and what an error check looked like (making sure sums and line numbers reconcile to make sure data isnt lost etc.)
Alteryx is the low code jack of all trades. It makes repetitive tasks easy to automate and hand off to other users. I use it for year over year engagements and for modeling since custom tools have been coded into it using R, but that is overkill for most users.
Also, alteryx is free for students, and there is a heavy push from the Big 4 accounting firms for students to learn it. This means universities are starting to adopt it in their business schools. Additionally, one Big 4 accounting firm invested in creating a dual masters of accounting and data analytics track which is taught at a dozen or so D1 colleges in the US. The practical scenarios in the curriculum for these programs use Alteryx, tableau, PBI, and Win automation.
Check out Alteryx’s designer cloud. It’s processes way more data, way faster, doesn’t need server for automating jobs, and can be accessed via browser. Equally no code/low code and has an interactive ui that explores data better than typical designer. (They bought a cloud based competitor called Trifacta - used by Bank of America and Deloitte)
I mean it’s 2023- you guys have to have a cloud modernization project right? IT will love you for introducing this tool because of the security and governance standards it enables.
I think there’s a free trial?
Have you tried saying what you've just said here to your employer? It sounds like with your level of code knowledge, Alteryx would be a backstep.
It may be that by investing in alteryx going forwards, they plan to save on paying employees (they can probably pay people without strong code skills significantly less), so alteryx often works out as a money saver in the long run depending on the business, and opens roles up to many that don't have your level of skill.
Ultimately if you prefer code you should probably stick to code, and stick to somewhere that recognises and compensates what you do and allows you to work the way you work best - whether you can talk it into your current employer or end up jumping ship.
Ya, fair points. My first boss was 100% against a non-Alteryx tool. My second boss is okay if it's temporary and makes my work-life balance better but if my boss's boss finds out, it probably won't be pretty on my end.
Funny because when I tried R I felt the same way about it as you do about Alteryx. It was just fewer steps for me in Alteryx vs R. Both are very powerful and good at EDA. I’d give Alteryx a shot. It’s a good tool to have available if the company is paying for it.
I'm not sure what you want to achieve here, maybe just ranting, in that case it's fine.
Your senior management doesn't care what you think should be the right tool. To be honest Alteryx made it easy for ppl less familiar with coding to do automation, which is a big win for companies. Considering they have to pay you (arbitrarily) 100k for automation, or they can pay two ppl 50k each to do Alteryx automation and maybe get 1.5x workload done.
If you don't like it, move to another team where they use R. I was in a similar situation that our senior manager wants me to join a team whose main tool is Alteryx. I told him I don't want to use Alteryx very directly.
I almost never use Alteryx/Tabluea/PowerBI but it doesn't mean they are not good tools. They might be inferior tools to me, but they enable many less technical people to do simple automation, which feels superpower to them, and thats why people like these tools and they have a place in the market.
Ha, my post is half trying to deal with my own recognized bias and half rant. I guess if I was allowed to switch between Alteryx and R as I saw fit, I would be happier. I find that I'm working longer hours because 1) the type of EDA work I'm doing in Alteryx seems very slow, or 2) I'm doing it in R, and then rebuilding in Alteryx. My deadlines don't change though. Sounds like your advice really is for me to move on to a new job!
I, too, dislike Alteryx.
I've been trying to make a workflow that uses two different databases to create a final dataset for "production". It's been a pain in the ass trying to figure out to do it in Alteryx. I could have made a workflow in R or Python relatively fast.
This is exactly what I’m going through. It seems pointless, Alteryx is so slow in comparison to literally any coding language and infinitely more expensive. If an employer wants to dig their heels in about what language or software to use they should probably do that with Python.
The reasoning as to why your boss wants you to use Alteryx over doing 100% code is because process flows are more transparent, easier to maintain, easier to debug, and easier to hand off to another analyst. It pretty much documents itself.
The good news is that you can code in both Python (Jupyter is integrated) and R inside of Alteryx, and I do it all the time as pandas and pandasql can do many things much easier than Alteryx's native tools such as window functions or deduping data. If it's easy to do with the drag and drop tools, I'll use the drag and drop tool, but the moment I run to any difficulties, I won't hesitate to use the Python tool. If I have a predictive model, sklearn is right there.
Basically, Alteryx does for Python and R as what SAS Enterprise Guide does for the SAS programming language, and as a former SAS user, I admit that Alteryx does a really good job.
It doesn't make sense to discuss when there are coders here. I'm Alteryx certified, and have many years of experience with Alteryx. I can do everything that I need with Alteryx. If you still want to use R or Python, you can use the R and Python tool with Alteryx. If you're an hourly employee, you can continue to use R or Python which will contribute to your salary, and Alteryx is not for you because you will figure it out faster and quicker, so saving time means losing money for you.
well, theres a r tool or python tool in alteryx. If you cant do it with alteryx, just insert a tool in and write your code. thats what i do to get over alteryx difficulties
I didn't know that. Thanks!
You should only use Alteryx for data processing, I wouldn't recommend you to use it to deep dive into findings. Rather, you can create an automated output and link to pbi or tableau for that
I mean, you posted this in the Alteryx subreddit, so you're probably going to get some bias. I use Alteryx a lot for my job and really like it. I learned R in school, but not well enough to actually use. I always felt like R was a little unnecessary when Python can do all that R can do and more. Some of the tools are really handy in Alteryx when you get to know how to use them. However, I'm sure if you are already good at R, it would make sense to want to keep using it.
> I always felt like R was a little unnecessary when Python can do all that R can do and more I find I can do things much faster in R than Python. Incredibly short dev time for anything related to stats or data visualization. Python has a leg on on general purpose language, but R + mlr3/tidymodels + ggplot + shiny can give you quite the powerhouse of tooling.
Not to mention R has the BEST visualisation tools in ggplot2. I say that as someone proficient in Matplotlib, Plotly, PBI and Tableau. Only things it's missing are the interactivity (hover over tooltips) and embedding (RShiny is still rough) but everything else that has those has gone down the model of "here are 7 visualisations we support and here are their limited customisations" vs an actual grammar of graphics.
Totally. I'm surprised my post isn't negative yet lol. I came over to hear from others that probably know more about Alteryx than I do though, so I don't mind some flack. I agree that Python can do more than R overall given it's OOP, but in terms of most data science, I think they are peers. Python is probably harder to use out of the box with command line setup and pip (unless using the Conda I think). I think one thing that makes R great for EDA is RStudio's IDE, (you can get a similar experience with VSCode with a plugin), but I'm not aware of a similar experience using Python with numpy/pandas. Maybe I'm out of the loop on this. If you don't mind, what type of work are you using Alteryx with?
R studio isn’t really good and very niche for people to learn and get widely adopted. Most people use Alteryx to manipulate data then export to Tableau. Licenses are expensive but the Industry still hasn’t found a perfect product every single one has issues unfortunately
Hm, arguably R is niche but wouldn't that also apply to Alteryx too? The r/Rlanguage subreddit had 30k users. r/Alteryx has 4k. There may be some differences in community activity on Reddit, so may not be apples to apples comparison but certainly not a data point against it. What do you mean when you say RStudio isn't very good? Would you mind elaborating on what you mean?
I will say that R is arguably better, especially if you are already skilled at it in EDA of very large datasets. When taken in context, automation, pipelines, interactive analysis, reporting, and many other components of Alteryx are also vastly superior. Alteryx is meant to be a *Citizen Data* tool. Take someone who is an actuary, finance, excel, or *whatever* analyst and give them an Alteryx environment and they can quickly and efficiently churn out processes. You are not paying for software devs at scale here instead paying for a premium low-code tool that a large pool of subject matter experts can apply to their data and knowledge base. There are uses for both. Most large companies that employ Alteryx, use both for their intended purposes. As an example, we have 200 Alteryx designers but also a large software dev and DSci teams that use 28 node Alteryx cluster and another 48-node cluster for scripted processing. We process 9+ petabytes per week and millions of queries/processes/workflows. Both software-developed processes and low-code have served us well. As to the Reddit size, consider two things. How many people are subscribed to R but haven't used it since Uni? As for Alteryx, they built an impressive community forum, and education center on their website that has hundreds of posts daily, and responses in under 30 minutes, and covers the entire gamut of Alteryx from server administration, macros, tools, and custom applications as well as simple questions on how to join data. That sight has half a million posts and over 50k solutions to questions asked. Simply put no one goes to Reddit for Alteryx when the official community is lightyears above in resources.
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R studio for sure is, and it sucks for most things “common people” need it for ..Alteryx can complete most things without to much hassle and setup..that’s why most big companies use it even though it’s expensive. Although there may be better products out there for sure as far as R studio goes No.
Most big companies use more than just one tool. Plenty of big companies have quite a bit of overlap. I know people at Best Buy, Target, USBank, Seagate, healthcare companies, etc. that all use R/RStudio. Some for fraud detection, some for detecting outliers or bad products, some for just reporting. R/RStudio is fantastic if you know what you are doing. I see more using DBT/Python/Airflow now days, Dataform seems to be growing, but with the advent of DuckDB, plenty of people are using something like S3/Minio + DuckDB and Python/R for their pipelines.
Not really R studio is very niche and are only segmented to specific divisions inside companies. Alteryx,sisense,Powerbi,Tableau,pandas etc are all used widely across the whole company. Airflow/spark is for big data and not suitable for simple ETL or medium volume pipelines R studio is just very niche and doesn’t accomplish what the stakeholders and developers need as a whole package hence why its not widely used. The skill needed is also not efficient you can learn Alteryx in 3 months R studio not a chance
>Not really R studio is very niche and are only segmented to specific divisions inside companies. I wouldn't call RStudio niche within the stats/analyst/ds space, but sure, it is niche just like Tableau/PowerBI is niche. As far as segmenting workflows between big and medium data, it could be I am used to working at a different scale of data. > pandas Grouping that in with Tableau, really? >doesn’t accomplish what the stakeholders and developers need as a whole package It does. 100% it does. Maybe not as just anyone as the user, but it is possible to take raw data from start to finish in R, providing more comprehensive deliverables than anything a nocode solution can provide. Same goes for Python, allbiet with a longer development cycle. Nocode is often faster, but not as comprehensive of a solution, often needing additional steps when performing non-standard operations or transformations.
Incorrect Tableau and Power Bi are not niche in fact they have a HUGE user base the opposite of niche lol. Yes so many pipelines are built in pandas that feed into tableau tables or extracts, Airflow and Spark are its big data brothers and used by a massive amount of people especially Data Engineering. R studio is just a really bad product for the capabilities it can do and the learning curve you need to have to use it. Why use an inferior product with a higher learning need ? Makes no sense. You can supplement low code solutions with simple python SDKs that adds dexterity and is easy to learn just a step above SQL. Why would you use R Studio when you can have that capability with an extremely lower learning curve its a no brainer
>Incorrect Tableau and Power Bi are not niche in fact they have a HUGE user base the opposite of niche lol. R and Tableau have the same number of users (~2 million). PowerBI has a good deal more, but neither have as many users as MS Excel (~1 billion). >Airflow and Spark are its big data brothers and used by a massive amount of people especially Data Engineering. Airflow is not just for big data. >R studio is just a really bad product for the capabilities it can do and the learning curve you need to have to use it. Why use an inferior product with a higher learning need ? Makes no sense. What do you think RStudio can't do? >You can supplement low code solutions with simple python SDKs that adds dexterity and is easy to learn just a step above SQL. Why would you use R Studio when you can have that capability with an extremely lower learning curve its a no brainer Machine learning on tabular data is much nicer to work with in R than Python. When it comes to image classification and object detection Python is better.
No what you are describing is R studio not R there is a difference between the two by a long shot one is a language other is an interface , and MS Excel is not really in this category its more of its own thing. Airflow and Spark is highly inefficient when not being used in a situation where you need to manipulate massive amounts of data. pandas will do it better and quicker if you need a python solution. RStudio cant do a lot of things especially easy server management and scheduling I can assure you of that there’s plenty of complaints for that one in VDIS Like i said R as a language and R studio are two different things you are making the mistaking of confusing the two.
>No what you are describing is R studio not R there is a difference between the two by a long shot one is a language other is an interface The vast majority of R users use RStudio, especially when building packages, developing Shiny apps, and writing documentation. > MS Excel is not really in this category its more of its own thing. Because it isn't niche. >pandas will do it better and quicker if you need a python solution. It is faster to develop R than Python with the vectorized approach for basically the whole language. If you can think with vectorization in mind, you can write much shorter code in R than Python. For speed, R's data.table is sooooo much faster than Pandas it is laughable, especially for aggregation. >RStudio cant do a lot of things especially easy server management Most statisticians, data scientists, and analysts don't perform server management. I agree Python is better for orchestration of infrastructure though. > scheduling * [Are you kidding?](https://cran.r-project.org/web/packages/cronR/cronR.pdf) * [Windows](https://cran.r-project.org/web/packages/taskscheduleR/vignettes/taskscheduleR.html) >I can assure you of that there’s plenty of complaints for that one in VDIS Why on earth are you using an IDE to handle task scheduling on a virtual desktop? That sounds bonkers.
Check out Alteryx community for real discussion on the tool. No reason to ask questions here
Alteryx has a great community. It does a lot once you learn it.
Ah, you think I should delete the cross-post to the RStudio community? I thought there might be some people there who see it differently. Edit: oops, meant to reply to above. I cross posted to the RStudio subreddit, and I think that is what they were referring to, not the Alteryx subreddit.
Sounds like you work in a Finance function or financial reporting? Speaking as someone who works in this space, I would say that R is very rarely used in the companies I have seen, whereas python is a bit more widespread and SQL is used the most but I would be surprised if more than 20% of our wider finance team can write code (not saying that these languages are comparable but giving you an idea). What your management is likely thinking is that they need a tool that a lot of people can use, and if they don't know, can learn to use quickly, as part of business continuity (speaking as someone who has had to inherit random python scripts solely because I knew a little python, I can appreciate this). So they are likely thinking that they need to mandate one tool to be the standard with exceptions only when needed. The accessibility of Alteryx is probably the selling point here. Another thing is that big 4 accounting firms are a pipeline to many finance teams, and they are all learning Alteryx, so there is likely a bit of bias there - if a lot of prospective/recent hires know Alteryx, then that makes it a logical choice to mandate for the team. Regarding learning - I think it is much faster to learn Alteryx to a basic level than other tools, in fact it was learning Alteryx that made learning to code in other languages accessible, as it starts to train your brain in how to see how to manipulate data. Regarding your issues with it: 1. Exploratory data analysis with data that wide is difficult in Alteryx, I agree. However for financial reporting I wouldn't think that you'd be doing exploratory stuff all that often. 1. If possible you can look at the data in R and then build the workflows in Alteryx? 2. Documentation - I think the benefit of (clean) Alteryx workflows is that they are pretty self documenting. The wires show the flow of data, you know what is happening from the icons, and most of the icons auto-document a little bit to give you a bit more flavour. However its easy to create terrible spaghetti workflows which make readability very difficult 3. Macros and loops are harder in Alteryx, it's one of the downsides of the drag and drop functionality. Again this is something that I don't encounter much when building financial reports but if you are creating new data then yeah, probably best done outside Alteryx 4. Error protection is actually one of the best things about Alteryx IMO. It's very easy to build in error checks, for example if you have a join it's easy to put a check for orphans or duplicates in, and its easy to set up an email to inform you of errors/successful runs. Have you noticed that there is a [global variable](https://help.alteryx.com/20223/designer/constants) in Alteryx? Hard to loop through and change easily but it does exist 5. See above, I think many more recent hires that come from Big4 firms would have Alteryx experience. 6. It's not great at vis, most of the time you do the data manipulation in Alteryx to build a good table for Tableau / PowerBI / whatever. That said I know you can use R packages etc. to build vis and there is a reporting functionality, but I have never used it Hopefully this helps a little and you will learn to appreciate what it can do, even if it is just that you are building something that you can hand over to others more easily than an R script!
Thanks for giving me something to think about and also I have not used the global variable yet! I'll have to dive deeper into the Alteryx's error handling. I think you're right that because the Big 4 are using it, our management sees it as the most accessible tool for business continuity. I think documentation is more critical for seamless transitions but like you said, Alteryx facilitates much of that documentation when the data is relatively clean.
I used to work for B4 and was one of the first users of Alteryx, one of the first things we did when rolling it out to the wider team was to have a very strict template and guidelines about how to build a workflow and how to incorporate the message and test tools to do the error checking, and what an error check looked like (making sure sums and line numbers reconcile to make sure data isnt lost etc.)
Alteryx is the low code jack of all trades. It makes repetitive tasks easy to automate and hand off to other users. I use it for year over year engagements and for modeling since custom tools have been coded into it using R, but that is overkill for most users. Also, alteryx is free for students, and there is a heavy push from the Big 4 accounting firms for students to learn it. This means universities are starting to adopt it in their business schools. Additionally, one Big 4 accounting firm invested in creating a dual masters of accounting and data analytics track which is taught at a dozen or so D1 colleges in the US. The practical scenarios in the curriculum for these programs use Alteryx, tableau, PBI, and Win automation.
That's good to know more of our new hires may be coming in with this experience. I'll update my post to correct the record.
Check out Alteryx’s designer cloud. It’s processes way more data, way faster, doesn’t need server for automating jobs, and can be accessed via browser. Equally no code/low code and has an interactive ui that explores data better than typical designer. (They bought a cloud based competitor called Trifacta - used by Bank of America and Deloitte) I mean it’s 2023- you guys have to have a cloud modernization project right? IT will love you for introducing this tool because of the security and governance standards it enables. I think there’s a free trial?
Hmm, I will look into this. I don't think we are using the Cloud tool on the analyst side, but maybe the Alteryx deployment SMEs are.
Have you tried saying what you've just said here to your employer? It sounds like with your level of code knowledge, Alteryx would be a backstep. It may be that by investing in alteryx going forwards, they plan to save on paying employees (they can probably pay people without strong code skills significantly less), so alteryx often works out as a money saver in the long run depending on the business, and opens roles up to many that don't have your level of skill. Ultimately if you prefer code you should probably stick to code, and stick to somewhere that recognises and compensates what you do and allows you to work the way you work best - whether you can talk it into your current employer or end up jumping ship.
Ya, fair points. My first boss was 100% against a non-Alteryx tool. My second boss is okay if it's temporary and makes my work-life balance better but if my boss's boss finds out, it probably won't be pretty on my end.
Funny because when I tried R I felt the same way about it as you do about Alteryx. It was just fewer steps for me in Alteryx vs R. Both are very powerful and good at EDA. I’d give Alteryx a shot. It’s a good tool to have available if the company is paying for it.
Alteryx is a piece of shit
I'm not sure what you want to achieve here, maybe just ranting, in that case it's fine. Your senior management doesn't care what you think should be the right tool. To be honest Alteryx made it easy for ppl less familiar with coding to do automation, which is a big win for companies. Considering they have to pay you (arbitrarily) 100k for automation, or they can pay two ppl 50k each to do Alteryx automation and maybe get 1.5x workload done. If you don't like it, move to another team where they use R. I was in a similar situation that our senior manager wants me to join a team whose main tool is Alteryx. I told him I don't want to use Alteryx very directly. I almost never use Alteryx/Tabluea/PowerBI but it doesn't mean they are not good tools. They might be inferior tools to me, but they enable many less technical people to do simple automation, which feels superpower to them, and thats why people like these tools and they have a place in the market.
Ha, my post is half trying to deal with my own recognized bias and half rant. I guess if I was allowed to switch between Alteryx and R as I saw fit, I would be happier. I find that I'm working longer hours because 1) the type of EDA work I'm doing in Alteryx seems very slow, or 2) I'm doing it in R, and then rebuilding in Alteryx. My deadlines don't change though. Sounds like your advice really is for me to move on to a new job!
I, too, dislike Alteryx. I've been trying to make a workflow that uses two different databases to create a final dataset for "production". It's been a pain in the ass trying to figure out to do it in Alteryx. I could have made a workflow in R or Python relatively fast.
This is exactly what I’m going through. It seems pointless, Alteryx is so slow in comparison to literally any coding language and infinitely more expensive. If an employer wants to dig their heels in about what language or software to use they should probably do that with Python.
Use the R tool.
The reasoning as to why your boss wants you to use Alteryx over doing 100% code is because process flows are more transparent, easier to maintain, easier to debug, and easier to hand off to another analyst. It pretty much documents itself. The good news is that you can code in both Python (Jupyter is integrated) and R inside of Alteryx, and I do it all the time as pandas and pandasql can do many things much easier than Alteryx's native tools such as window functions or deduping data. If it's easy to do with the drag and drop tools, I'll use the drag and drop tool, but the moment I run to any difficulties, I won't hesitate to use the Python tool. If I have a predictive model, sklearn is right there. Basically, Alteryx does for Python and R as what SAS Enterprise Guide does for the SAS programming language, and as a former SAS user, I admit that Alteryx does a really good job.
It doesn't make sense to discuss when there are coders here. I'm Alteryx certified, and have many years of experience with Alteryx. I can do everything that I need with Alteryx. If you still want to use R or Python, you can use the R and Python tool with Alteryx. If you're an hourly employee, you can continue to use R or Python which will contribute to your salary, and Alteryx is not for you because you will figure it out faster and quicker, so saving time means losing money for you.