Alteryx Reviews

We were analyzing data trying to find anomalies with the servers and things that were going wrong. Normally in what we do, it can be a very manual process looking for that kind of stuff. Therefore, using this product, I created a workflow that went out and looked across all devices for problems that are happening, and managed to cut down the number of issues that were being created daily.

The amount of labor that it takes us to find issues is pretty high. When you put the automation in place, that frees up your time to concentrate on the advanced analytics. We recognized right away in that first year that the amount of FTEs that we would have to acquire to do that work was a significant amount of money. It just stepped us into automation of many things that we do. That frees us up to be able to do a more mature analysis, and not that day-to-day stuff that you we have to track.

Not everybody's budget allows for having a team of 20. We just don't have that. It's saving us a lot of money in FTEs.

Right away we knew this has a lot of value, even from the perspective of data manipulation and automation. 

There are all sorts of use cases that we could come up with. It does take a little bit of learning and figuring out how to work the tool, however, we've been really successful with it. I even went and presented at one of their conferences our use case. 

Automation is the most valuable aspect for us. The ability to wrap business logic around the data is very helpful. 

It not only helps us with efficiency. You can also flip the steps apart to make that data flow in various ways. 

Most tasks run in less than two minutes and provide us with what we need very quickly. I can wrap rules around the data to look for certain things or to notify people. 

The amount of manual labor that we're saving by writing those workflows is huge.

The solution does have a bit of a learning curve.

I initially managed the product completely. Then, when the user base grew, another group just took it over. What they're struggling with is it's not as mature as Tableau in the user management area. It was tougher to manage the server part of it right away, especially since the user base has grown. When you get hundreds of users in there, trying to manage access to the product is a little tougher than Tableau.

I've used the solution for maybe around five years or so.

The solution is quite stable. It's not as mature as Tableau in that stability area, however, it's pretty reliable. We don't have a lot of problems with it. Initially, we created a lot of cases as we didn't understand how to best manage the product. Now, very rarely do I open a case with support and have issues.

They recently moved to a different support model. Initially, when we came to the product, the support was pretty good. Now, when we open cases, it seems not so good. They're asking customers to pay more money to get a higher level of support. Of course, due to the fact that we don't open that many cases, it's not important to us to get to that higher level. That said, the response time given and the attention to us is not as good as it was initially.

When trying to pull large datasets into Tableau right away we realized that we had to do something different. Prior to Alteryx being available, I would use scripting to stage the data. I happened to notice an ad on LinkedIn for Alteryx, and I thought, "Wow, this is exactly what I need." I talked management into buying it. I was the first one in the company to start using the product.

We used outside vendors to come in and help in certain parts of the implementation.

It's more expensive than Tableau, for example.

There has been some scrutiny on the overall costs. We're trying to go to more open-source, with more products that don't cost so much. I have to continually work with folks on proving that the value of what we pay in licenses.

The solution has recently changed its support process and is now pressuring users to pay for a higher level of support services. That could potentially be an extra charge for some companies. 

We are just customers and end-users.

I would advise other companies considering the solution that the training is important. They've been great working with us on free training for this, that, and the other. The company really does provide a lot of those resources. The community is very good. The knowledge base that's out there in the community is great. A company should just tap into that and any free training they can. It takes a little bit of time to get proficient at it, however, the payoff is there.

Overall, I would rate it at a seven out of ten.

In our team, we use Excel for a lot of calculations and automation workflows. We retrieve data from the database, perform calculations, and then distribute the results to various departments or customers.

Alteryx helps me do a lot of automation. The best thing about Alteryx is that you don't have to repeat the workflow over and over again. Unlike Excel, where you need to write formulas for each new file, Alteryx follows a consistent process. You can schedule and automate the workflow, even if the files change.

I think sometimes the solution doesn't load properly or takes so much time for the workflows. Though the workflow runs and completes the file in Excel, if you use the same formula, it's a bit slow. Also, the image processing is not so good because I tried to do some image processing and they were like, sometimes they put two to eight. In the document, it was two, but the OCR predicted it as eight.

I have been using the product for two years. 

The tool is stable. 

My company has more than 100 users. 

I haven't contacted the technical support. 

The tool's installation and setup are not difficult; you just need to install it.

You can use this tool if you want to do a lot of automation. It is easy for users to learn and use it. The drag-and-drop interface works fine for us. I rate it a seven out of ten.  

We use Alteryx to modify and modernize data based on different types of data requests. The data and the data source may be in different forms, resulting in unstructured data in the database. We use Alteryx to give good shape and size to such unstructured data.

Alteryx makes it easy for the end customer to see clean data in a structured form. Alteryx has many features, such as info data, data cleansing formula, the select tool, union, summarize, and text-to-form. We use Alteryx in the database for reporting, documentation, email, and data preparation.

To use Alteryx, you need to think like the people who write software codes. The formula we currently use in Alteryx can be automated. This would be helpful for people using Alteryx who are not from a coding background and can write the formula differently. Whoever is using Alteryx should feel some convenience using it. We found most of the useful features built into Alteryx, but they all are on a paid basis.

I have been using Alteryx for nine to ten years.

I have not faced any challenges with stability.

Alteryx is really scalable. It adds value and fits our business. More than 300 users are working with Alteryx in our organization in India. I do not have the exact figures, but 2000 users globally use the solution in our organization.

During COVID, they had on-call engineers for very good technical support. I would like to have that support again because they have now closed it, which is difficult for people who need it. They should continue that kind of support again. It would be good if they could provide technical support on screen.

We did not use a different solution but we are planning to use Google Cloud Platform.

The implementation is not a big thing for Alteryx. It is simple and easy to use.

We have seen ROI with this solution. However, if we explore other tools in the market, we will probably get a better ROI.

The solution has a more costly license than other tools in the market.

Alteryx is the best solution for people who want their data in a structured way. It is a bit complicated for a new user. The complexity of the tool is evident by the fact that only if you provide an exact input to this tool it will give you the output. However, if you know a little about Alteryx, it is a very good tool for you. We are using an on-cloud deployment for this solution.

Overall, I rate Alteryx a seven out of ten.

The use cases range from basic EPL to predictive analytics and spatial analytics.

For example, within our functions group and our larger finance organization, we have a number of use cases where people are doing a lot of manual work, mostly in Excel. This has enabled us to move away from that, resulting in not only streamlined processes and efficiencies but also a significant increase in our ability to have confidence in that data. If the need arises, we may need to refresh data or revisit something.

It essentially automates what would otherwise be some extremely tedious activities to rerun and re-perform.

I believe that the ability to leverage the gallery for scalability, as well as the general data blending functionality, is most beneficial to our core-based users. Obviously, there's a lot more to it, but these basic data prep and blending tools help us a lot.

In some ways, I believe it is not yet as integrated as it could be. I believe that the data integration inquiring component could be improved slightly.

The data integration component could most likely be improved to increase enterprise scalability.

I have been working with Alteryx for two years.

It varies, but it will be the 2021 version.

The stability of Alteryx has been great.

It is highly scalable for the vast majority of things you want to do. When it comes to extremely large data sets or very specific analytics that would be delivered at an extremely high scale, either really, really tremendous scale or tremendous volume may be problematic. However, those are only a small number of possible scenarios. As a result, it hasn't been a problem for us, but we've switched to another technology for those types of use cases.

The roles are extremely varied. We have over 100, and less than 200, but that will increase in the coming months.

We are currently at capacity in terms of licenses. So we're looking to go from the low triple digits to over 1000 in the next year, maybe a year and a half. I believe we will quadruple in the coming year.

Technical support is quite powerful. I believe you must know how to take advantage of it, but I believe they have the necessary infrastructure in place to get you where you need to go. I believe it is somewhat incumbent on the organization to have someone serve as that contact, that partner. They're fine as long as you keep your end of the bargain.

We switched because we wanted to. We didn't have anything that could do everything Alteryx did, in my opinion. We had some minor transformation tools and such, but nothing that could truly compete with Alteryx.

The initial setup is straightforward.

That's something we're still working on. We started with about 100 licenses and identified areas where we thought it could add value. That has been demonstrated, and we are working to scale significantly over the next year. It's been a two to four-year journey from discovery to widespread adoption.

The majority of the work is done in-house. We initially worked with Alteryx, but it was primarily done in-house.

It has certainly paid for itself on a per-user basis. We haven't done a group ROI yet. But it more than pays for itself. Our "highlights" are quite powerful. The more prominent business cases are extremely compelling.

It's not cheap, but they offer a variety of packages to help you grow in practices and programs that allow you to scale effectively while also testing how deep the use can penetrate while allowing you to really reduce the risk. They offer various bundles in which they offer free licenses as well, so you can essentially see if you're able to use them consistently. Then, the next time, you can add that number or various other programs. It's probably on the pricey side, but they provide some really useful ways to grow and test.

If you're serious about scaling, you'll need a product manager, which is a major cost aside from the license.

We evaluated other products.

Simply strike a balance between democratizing the use of data transformation and analytics and having a vision for how you might want to roll things out. I think it's not the easiest thing to strike that balance, but that's my recommendation. To try to have a plan, but also to make sure you're not putting up too many barriers.

I would rate Alteryx an eight out of ten.

At the time, I used the solution for data preparation and data handling, which is cleaning the data and then working with the data, and linking different data effects. 

The solution is on-premise. I use it on my desktop.

Alteryx is great for someone who doesn't want to program and doesn't fiddle too much with the machine learning algorithms. If you need to do sophisticated things (if you're a real data scientist), then Alteryx is not the right way to go. For most users, there is plenty of capability and that's enough for more mundane use. The solution is rich and very flexible.

They have the capability to integrate some oiutside coding, but I didn't invest enough time to understand how that can be done and what the limitations are. If someone needs to do it, I'm not sure if they will be able to save time in the process or if that is cumbersome or not. I haven't tested whether or not integrating R code is flexible enough to accomodate specific developments with both platforms. Integrating optimized algorithms for the sake of automation would be great.

The biggest limitation is that the solution doesn't allow you to do sophisticated things in terms of fiddling with their implementations of machine learning and deep learning components.

I think they should really work on integrating or have a capacity to integrate tailor-made algorithmic code. I think that's one of the most important things they need to be doing.

Alteryx is very stable.

I haven't needed technical support, but they seem to be very available to talk. The people that I spoke to in Alteryx were very reactive and present. The moment you download the software, someone will call you, try to get in contact with you, and try to understand what your needs are.

I only installed the desktop and it's like any PC-type software. It's done in a few minutes, so it's easy. The server part is something else, and I haven't tested it so I can't elaborate on it.

I tested the solution for a long time so I never actually bought the software, although Alteryx is very costly. In comparison, KNIME is free.

To start with Alteryx, you need to pay for the desktop. The desktop platform costs $5,000 per year. You probably get more support with Alteryx, and it's good for non-sophisticated users who can benefit from the support included in the price.

KNIME is probably the alternative to Alteryx for someone who needs a package. The package can do a lot of things without needing too much programming and with zero code. It's very good for someone who needs access to algorithmic content without needing to develop it. However, I don't have concrete experience using it.

They are both very good packages for someone who wants to develop dashboards or use algorithms without knowing the nuts and bolts or with limited coding. They are very practical. The difference between the two platforms is very limited. They are equivalent.

I used Alteryx for data preparation, and KNIME can do it just the same. The two are very close in terms of concept and the way the two softwares work, but there are lots of tools for data preparation. Right now, I use a lot of loose programming. I develop scripts with R, and that is the most effective way I've seen because I can do whatever I like. I have 100% flexibility.

I think that a real data scientist would go with R or Python and use Spark. It's a totally different world, and these softwares need much more investment in time and effort to understand how to use them. It's a lot of work, whereas Alteryx and KNIME are for the casual user. They are more for the people who are in companies and need to work on data without clearly understanding the mathematics behind it.

I would rate this solution 9 out of 10. 

Alteryx is the kind of software that a corporation would want to go with and to deploy on for people who are not really data scientists and that have to use data, design dashboards, have to clean and prepare data and so on. That's an effective way to use Alteryx. To go for a sophisticated data science type of added value, a data scientist would want to work with programming languages and use a lot of the libraries that are available. At some point, they would want to put all this code and integrate this code into the platform so that less sophisticated users can use the analysis done outside operational lines.

This is definitely the kind of software that is a time-saver if you want to start working on different data sources or a lot of data sources, and you want to work with the data, angle the data, cross-link and so on. It's very good and very easy to use. It's visual, so it's easier to understand what you are doing. When it comes to putting some intelligence into it, it's enough for most people. There is enough that is loaded into software that can help you. The Alteryx interface may be easier to understand than KNIME. You are able to do some nice things with it in just a week.

I believe we are using the new version. 

I use the solution for development and certain financial projections, such as making a business plan. I employ the solution for the amalgamation of big data. 
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I also use the solution for certain analytics deployment, such as that found in the commercial arena, for ascertaining the projections of sales. 

I like the solution's velocity, the speed with which it processes data, and its ease of use. It has good usability. 

A colleague of mind mentioned that the solution should have more options for the visualization of data. The visualization filtering could stand improvement. 

The documentation could be improved upon. 

The price could be better. Though we are satisfied with the solution, we feel the price to be a bit on the expensive side. We make use of another ETL solution, the PowerCenter. We would like to improve on and escalate Alteryx, but find it too expensive at the moment to do so. 

I have been using Alteryx within the past 12 months. 

I believe the solution to be stable. 

I believe the solution to be scalable, although I cannot say for certain, owing to the price. It We are not talking about a corporate solution at the moment. While we wish to improve upon and escalate the solution, I believe it is too expensive for us to do so at the present time. 

While I cannot speak about the future with certainty, we do have plans to increase the usage. We are satisfied with what we have at present. My area currently consists of four licenses and we would like to improve on this, to have more users. For the moment, we don't have definite plans to buy another license, certainly not in 2022, although, perhaps, in 2023. I sure hope so. 

Technical support is good.

We make use of another ETL solution, the PowerCenter.

We also make use of Databricks, which we use as a data science platform, although I cannot say how this compares with Alteryx. We use Databricks as a corporate ETL solution from the Data Lake. 

We use Microsoft Azure, as well.  

The initial setup was easy.

The deployment was fast, I believe lasting one day. 

We handled the setup on our own. 

I don't know how many people are needed for deployment and maintenance. 

The price could be better. Though we are satisfied with the solution, we feel the price to be a bit on the expensive side. We make use of another ETL solution, the PowerCenter. We would like to improve on and escalate Alteryx, but find it too expensive at the moment to do so.

The licensing costs are around 26,000 reals, perhaps $6,500 a year.

The licensing is all inclusive. There are no further costs. 

I don't make use of Alteryx myself, although my area, of which I am a manager, does. 

I am a customer of Alteryx. 

There are six people making use of the solution in our organization, two from compliance and one a data scientist. 

My colleage rates Alteryx as a nine out of ten. She says she loves it. 

I am using the product for making machine learning models for particular uses that we have to focus on analytics.  

I didn't like the data analysis features at first, but they were actually quite good. The built-in machine-learning models that they have are quite extensive and useful. There are a few models that are normally not found in any other drag-and-drop interface platforms. For example, when I was using and testing other tools, I could not find vector autoregression models. I also could not find the rather complicated tentative models and other model types that I find very useful. Those are built-in to Alteryx as cubes. On top of that, the capability of writing Python commands and creating our own tools and our own models for machine learning make the solution customizable and quite interesting.  

There are a few ways the solution could be made better. The graphical user interface could be made more friendly. I mean from the GUI point of view, it is a little dated. But from a functionality point of view, I think even for people who do not know the coding part and who are more business users than programmers, they would not have a very hard time using  Alteryx for creating machine learning models. It is quite good and quite useful already without improvement to the GUI. It could just stand to be more modern-looking. 

I would like if they could make some type of free license for the product. Not a free full license but a limited edition or limited capability free version. The limited-time version is a little restrictive. A free, open-term desktop version like Power BI and Tableau and KNIME might help users more with discovery and utility.

I've used this solution for about five or six months.  

We were using Alteryx from a development point of view. We did not use it to test it to its breakage point. So it handled our demands and was quite stable.  

The response time was quite good. Even running on a laptop, it was like using it on my desktop. The response is consistent, fast and stable.  

From my experience and from my point of view, the solution is quite scalable. We did not use it for the production system yet, but from my experience of using it on a laptop more recently, it runs with a few hundred thousand rows and columns without a problem.  

The other good side of the scalability is the number of connectors available for data sources. They have more than 200 connectors, which allows access to well more sources than anything I have needed.  

I did not contact the technical support at Alteryx directly. When we initially got the license, they had us talk to the local support here in Singapore. We went to them for a small issue to see what exactly the product can do and then we did not need any support from their support at all. We are quite adept with this solution and modeling. We called up the Alteryx local support to show us how to do that one thing but it was very easy. Once we saw it, we did not have additional reasons to contact them again.  

Before Alteryx we tried of KNIME. The learning curve for KNIME is steeper than Alteryx. Alteryx is much more user-friendly than KNIME, at least from our experience on both products. Also, KNIME functionality is limited for the free version so it was harder to explore the full capabilities. When we tried the free license for Alteryx, we got the full use of the client license for 14 days and then we were able to get an extension to explore our testing of it for some time. But we did use KNIME before that for long enough to be familiar with the differences. My impression of Alteryx is that it is more user-friendly than KNIME and the built-in modeling in Alteryx is much better than KNIME.  

The initial setup was very straightforward. I was able to install it and get it running up and running quickly and the process was very simple.  

When I started doing a machine-learning model in a project writing my own code, it took me in-all about three or four days to complete it. For my initial experimentation, I decided to replicate that model in Alteryx. As someone who understood models but did not know the program at all, it took me two hours or less than that to complete the test. Once you learn how to drag-and-drop things in the interface, it is very easy to start on development as long as you know what you want to do.  

We did not use any help as far as an integrator, reseller or consultant. We did the deployment ourselves.  

Our approximate cost as we understand from the company is that the total is $5,000 per user per year for the desktop production license. So, for us and the ten licenses we need, that means the production license would be around $50,000 per year. That might not be the exact number, but I think it is close enough to be correct. With that, there are not any additional costs. Probably you can pay for support and for training if you want something like a dedicated workshop. That might cost more as an add-on but there is no additional cost for using the tool itself.  

I have a really good impression of Alteryx at this point in time. So I would suggest to people who are considering this type of solution to go ahead and try it. If you are looking for a self-service data analytics tool, Alteryx is a good solution. It does a good job of end-to-end integration as well as accessing data from multiple sources or email modes. Then you can push data out to Tableau and Power BI or tools like that if you need other capabilities. So, 'go ahead and try it' would be my recommendation.  

On a scale from one to ten where ten is the best and one it the worst, I would rate Alteryx as easily a solid eight. From my use case and considering the point that I'm not seeing and using everything, I can't give it more or less. But from our use case and what we have in our company, it is pretty good for several purposes.  

Right now we have huge amounts of data metrics. We have a marketing team. We have sales. We have a networking team. We have door-to-door. In terms of data preparation, this solution was the primary method to get the data from many sources. It is easy for us in terms of integrating with the cloud and we can do most of the preparation. We can enable Alteryx to handle our data preparation, and sometimes you can enable it to set a pipeline and it can be stored in CCP. We mostly use it for working with Tableau. We're currently running it for multiple use cases.

The best thing is that the product is low-code and mostly no-code. It can be used dynamically by both customers and the internal team also. 

In terms of speed and reliability, it is comparatively good and actually leads the pack in terms of competition.

It is easy to set up.

The cloud deployment ensures it scales easily.

The solution is extremely stable.

The solution is improving continuously. They have, for example, just added automatic insights. If they continue to improve on their overall service offering, that would be ideal.

I've been using the solution for quite some time - almost four years. I used it when it was being a stand-alone application and now we are using Alteryx Cloud with integration to Trifacta.

The solution has been highly stable and reliable. The cloud is very stable. There are no bugs or glitches, and it doesn't crash or freeze. 

We have 200 to 250 people working with the product in my company.

We faced a few issues with scalability in the past when it was a desktop application. However, after we started to use the Alteryx Analytics Cloud, this application has been really stable in terms of scalability. Initially, we started the trial with 30 people. Now we have around 200 to 250 people who currently use Alteryx Cloud. It scales quite well for us now.

We have a special SME which is assigned by Alteryx to our organization. If we have any problem, we reach out to them in terms of any support. Mostly, myself and my team have never needed to connect with tech support as it is highly stable. The only thing we've had problems with is having issues around how we can automate the workflow. When we have questions like that, we just check with them.

We've been testing RapidMiner for quite some time. We wanted to have another option in pipeline if there happen to be any stability issues and budget issues happening or if the cost of Alteryx becomes an issue. However, in terms of RapidMiner, we have not fully used it for multiple reasons.

The initial setup is very simple and straightforward. I've used it for a long time and previously used it as a desktop application. While it was simple then, now that they've moved to the cloud, it's even easier. 

The solution is now quite expensive. You need to have a budget for it. However, if you do, it is worth the cost.

We're a customer and end-user.

We are using the cloud deployment and, therefore, always on the latest version as it updates itself. 

I'd recommend the solution to others.

I would rate the solution nine out of ten. It's been highly useful for my organization in terms of data strategy. In terms of usability and scalability, Alteryx is the best.