Alteryx Aggregated Reviews
We use Alteryx to pull data from multiple sources, blend it, modify it, and create calculations. We can then export to Excel or connect the results to Tableau for visuals. There is also a scheduling feature too (which costs more). The costs are high so it’s probably not feasible for your needs, but it is a pretty powerful tool that most users can learn pretty quickly.
Alteryx really depends on your application. If you are doing ad hoc interactive work, it works great. If you are designing an etl to be productionized and to be debugged and expanded over years, Alteryx is a massive pain.
I’ve put a lot of time in to rewriting other people’s Alteryx in something maintainable.
I’ve been watching Alteryx for a while, and in the past 12 months, they’ve been incrementally “ Tableau -ifying” themselves. Off the top of my head: they’ve restructured their pricing structure significantly, they’ve made the designer much easier to download, and they used to have a “Demo” version that was fairly hobbled, and they’ve moved over to the tableau way of selling via proving value in 14 day free trials. Additionally, they’ve also put “free” training on their website and tried to set up a community. But, if you’re thinking “Well we got this agile reporting for the business user solved, now let’s look to Alteryx to tackle ETL and PA the same way”, it’s not quite that simple. I even saw it at Alteryx’s conference this year. Lots of Tableau -like things, but not quite sticking the execution.
Speaking as someone who formerly had to do a lot of data prep using MS Access, Alteryx has been revolutionary for my needs. A workbook I’d designed that was reading two data sets (one 500K records and the second about 100K records) took Tableau about 4 minutes to read and render when those tables were stored in an Access database.
Because Alteryx can output in .tde format (or directly to Tableau Server), and because it has handy tools to tighten up your field sizes, I was able to get the workbook to the point that it could display the same sheets in about 10 seconds.
It sounds like you may not need it if it doesn’t fit your skills and style, but for me it has been a godsend.
Alteryx is a fine tool, especially for prototyping and building desktop-type data flows. It’s also designed to be really easy to learn and use.
Someone who understands working with data – joining, filtering, transforming, etc., can pick up Alteryx in a day or two. So I don’t see a lot of value in making Alteryx itself a requirement.
My exception to that might be if you have significant projects built in Alteryx that involve trickier aspects like it’s R integration, etc. and you need new people to hit the ground running with all the “deeper” aspects of the tool.
Also note that Alteryx (at least used to) provides training. I went to their HQ for a 3 day training session that was really useful. I think they’ll also send people on-site to train your people if you have enough of them.
I was a hardcore Alteryx user, but I moved to a company that wouldn’t pay for it. I learned Python and I ultimately like it better.
The benefit of Alteryx is a faster integration and selection of a variate of sources. Do you have 2 databases, 3 csv files, some excel and xml that your just want to integrate quickly for proof of concept? Altertyx will help you do that faster.
Alteryx is for people with a lot of ad-hoc integration work on a lot of sources, or people with weak programming skills.
Pandas offers 90% of the speed, Alteryx offers 90% of the flexibility. One is free, the other has a price tag.
As a daily Alteryx user, I’m going to try to avoid listing pros/cons of Alteryx as software (that’s a different thread!) Thinking specifically about Alteryx experience as a job requirement:
Alteryx is expensive, which is a barrier to adoption. Listing it as a requirement is going to reduce your candidate pool. We use Alteryx daily on our team, but don’t list it as a requirement for new analysts (we usually list it as “preferred”).
OP, you said this is a data analyst, not a data scientist position. Programming skills are not usually expected for a data analyst, in which case Alteryx is a plus. I would fully expect a data scientist to have the coding skills to perform the same steps without a drag-and-drop tool like Alteryx.
Alteryx experience is less important if your data foundation is robust (i.e. you have a fully-stocked, accessible, well-laid-out data warehouse). If analysts have to work with different inputs (Excel, CSV, JSON, etc.) that need a lot of manipulation (and the candidate does not have programming skills), then Alteryx experience would be a plus.
I swear by Alteryx. I have yet to run into an issue or a problem it cannot solve.
I’m a data engineer so take my opinion with a grain of salt as I prefer working with code opposed to a GUI. My company has Tableau and I’ve demoed Alteryx extensively. Tableau is good at building interactive dashboards for large data sets. In my personal opinion, most of its graphical capabilities are sub par compared to python or R, but it performs well with big data sets. Alteryx on the other hand I would not recommend for a data scientist. For a data analyst, absolutely but a data scientist should be able to build a high performance model which most likely means using something like python or Scala. Sure Alteryx could do some or most of your tasks, but you will be missing the opportunity to perfect your ability to work on the tasks it can’t handle, which is likely to be more valuable to your employer.
Alteryx is nice but the lack of Mac support is a bummer.
Alteryx is a great tool and is generally faster to use for most tasks than building out the same process in stata or SPSS or another data tool/ language. It’s also generally, but not always, easier to debug the workflows. It’s very expensive so if you have the chance to learn go for it. Also certification is free.
I had Alteryx install on my computer for several months while my company was demoing. I didn’t find it useful at all, but then again, I was not it’s target customer. I receive more static datasets and reoccurring tasks are not very common.
I think it excels at maintaining complex data pipelines, visually showing you how data is mixed/matched and processed. You can choose to rerun a single step in your pipeline or the entire thing. You could conceivably just switch out the original data source every year (i.e., 2016 to 2017) and keep everything else the same. Redevelopment should be fairly minor (but couldn’t you say that about anything?)
It also has some fancy data packages that come with it if you need to do any marketing data append or geocoding.
So my team uses Alteryx and Tableau . I’m the only person with an R background. I’m at work still, so won’t dive too deep right now into responses.
Alteryx is not a database nor can it function as one. It can read from and write to databases, among other data sources (APIs, excel, TDE if you fit it just right, etc.).
Its visualization capabilities are admittedly lacking, especially compared to Tableau . Honestly, we don’t use them (except the Network Analysis viz output via HTML5). In terms of data prep, we’ve found Alteryx to be a lot better than Tableau and we dump output into a new table for our dashboards to read from.
You should be able to look at the predictive tools package online to see what there is. There is a bit of stuff. A lot of these are built in R, so you can open up the tools to see what’s going on a bit underneath. There’s also run commands and an R console to be able to build what isn’t there. I can’t really give more on these as Alteryx thus far has been used mostly for data prep that is too complex for Tableau to handle well.
Alteryx does have the ability to use typical SQL queries as long as they don’t contain temp tables (this has been my experience). Joins are similar, but more like a Venn diagram and you select which of the pieces of that diagram you need.
It can be done as easily as a SQL query. If it’s a small change, it’s typically been really easy. I have not had to redevelop any workflows unless there were significant logic changes.
Alteryx is obviously not perfect, but it has been fairly user friendly so far. I was able to pick it up fairly quickly and it’s been spreading like the plague among other teams responsible for reporting. It’s proving far more valuable to these other teams, as we aren’t purely analytics and/or reporting. I know the main advocate within my company for it would previously spend a full week validating nasty SQL queries and had reduced that time to about 2 hours with Alteryx (I believe this was the number he gave, we’ve had it nearly a year now).
If this is something you’re considering, I’d honestly recommend reaching out and getting a demo. They’ve been wonderful to us in providing temporary extra licenses, providing training to those with licenses and even slightly interested and have done workshops where we brought our own use cases.
Changelog – pre-ecosystem era
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v0.1.6 GRIN tech affiliate program is live.
v0.1.5.3 GRIN jobs experiment started
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v0.1.5.1 GRIN games emerged
As a web agency we never could and never will be able to escape the urge of building things.
Among million other things we played with an idea of text-based games and the last piece that was missing was the story itself. So via in-house outreach platform we found two established writers that believed in the project and agreed to participate.
Shout out to Richard Abbott who wrote Fraud on Thetis and Eva Pohler who sent us a huge draft we are still reading through.
At some point we realised that list building, fetching contact details & outreach tech work just as well for b2b lead generation
v0.1.3 Once, we fell in love with ecommerce, because of short feedback cycles on marketing & development efforts.
Today we ship into production inhouse SaaS project - AVOKADO - the web app for learning languages with flash cards.
The year after we built it we realised how long is the road map ahead & what resources we'd need to promote it and decided to put it on hold.
One day as we ship GRIN tech v3.0 into production we'll distrupt the language learning market with Avokado.
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