Alteryx Reviews

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.

Alteryx is the ultimate replacement for a data shop. I use Alteryx in place of a data center.

We using Alteryx on-premise using gaming systems for performance.

The most valuable feature of Alteryx is its unlimited handling capabilities.

Mastering Alteryx, a comprehensive solution, takes time. However, once you have gained proficiency with its layout and how to drag, drop, and connect components, it becomes remarkably easy, yet still thorough.

The visualization could improve in Alteryx. It is ideal to use another solution, such as Qlik, to make up for the lack of visualization.

I have been using Alteryx for approximately five years.

The solution is scalable. To scale the solution you will have to add more hardware to the on-premise setup, such as CPUs and memory.

We have received a return on investment using Alteryx after the first job.

The cost of Alteryx is approximately $2,900 annually.

When I first started using the solution I was working with the state and was given six years of pregnant women and children data and it took 35 minutes to process the data. I tested the same data recently and it took .3 seconds.

Data should be returned within 30 seconds to make to process useful and if the solution does not provide this, then it is not beneficial.

Cloud deployments are not as quick as the on-premise.

I would advise others that they need someone who understands their domain in terms of the field that they are in. They need to have someone to hold their hand for the first ninety days. Once they pass the ninety days they will be set for the future.

I rate Alteryx a ten out of ten.

The biggest use case for the solution is that it allows you to it allows me to combine data from different sources and different formats to create a unified data set to answer business questions. I can take data from my general ledger and combine it with my expense report data or with external data or with different parties or different questions, and it could all be in a different format. For example, one source can be from a database, one can be an Excel file, one can be a PDF, or a CSV file. Alteryx lets me very easily put them all together and create one database. 

The biggest thing I like is that you need zero coding experience. I'm not a coder. I'm an accountant by trade, and I've been able to pick up the tool fairly quicker, basically.

The tool is very drag-and-drop. The tool has very good documentation to help you understand the features.

The community is very active and helpful.

I like that I can merge data from different sources into one place. 

With this solution, we can do reporting in about five minutes as opposed to day.

Once we've vetted the data, we can get the solution to run during off-peak hours so we can out data very easily. 

There's a lot less maintenance required.

We like that we can make notes right on their Canvas, so it's easy to pass workflows over to other users.

The visibility is very clear. We can show what data is being used and how it is being transformed.

My true data is able to stay intact even though I can easily manipulate it. 

I'd like it to be easier to work with PDF. When you want it to read PDFs, it can be a bit difficult. That may be a PDF issue, however. 

Maybe if I was doing more spatial or geographical tasks, I might need a bit more; however, for my purposes, I have all the features we need. 

I've been using the solution since 2017 or 2018. I've used it for five to six years on a daily basis. 

I find that the Designer is stable since it's on my machine. Sometimes the server environment is not the most stable. I'm not sure if that's due to the fact that we don't have enough cores or whatever that might be; however, that's something that's probably a little less stable, the server at the bottom. Again, the servers will be used to run flows, not to create the flows.

The Designer is where you create the process and your logic, and you can use a Server to run the processes at different times throughout the day.

The scalability is fine. That said, the pricing model is not the cheapest. You have to be careful who will be using it. The pricing is the only hindrance to scaling. 

We have around 300 to 500 licenses. It's pretty mature in our organization. 

We have a great relationship with technical support. They are helpful and responsive, and they have a great community.

I'm not sure if the company used something previously.

In order to deploy it, you need to have Alteryx Designer. You have to have that installed on your machine. We have a yearly license and you just basically renew your license with Alteryx to keep it active. 

In order to maintain our flows, there is very little maintenance needed. 

We have witnessed excellent ROI. The fact that we can schedule flows and reduce time and entry to market has been extremely positive for the company. 

The pricing is reasonable; however, if you need a lot of licenses, it will get expensive. 

I am not using the latest version of the solution. We're always one or two versions behind the latest, as we only do updates once or twice a year. 

The great thing about the solution is that if you know Excel well, it translates very well into Alteryx. It's important to have an open mind; however, I'd recommend everyone give it a try. 

I'd rate the solution eight out of ten. 

I used Alteryx for a retail company's project. They wanted to generate quick results out of some analysis for their fast-moving products and manage customer profiles for starting campaigns only for these fast-moving items.

Alteryx enabled us to develop models and perform core Python coding, utilizing different approaches like the waterfall and agile frameworks. We sometimes use the SAFe agile framework.

I found Alteryx's ability to modify data on the fly, using in-memory processing, very useful. This feature prevents the necessity to store data temporarily. 

The tool also provides functionality for dashboarding, report bursting, and handling multi-currency and multi-language situations. It helps in managing delivery for large teams.

It would be beneficial if Alteryx could lower its price or introduce a loyalty program for individual consultants and freelancers like me. It would help independent users manage projects for clients without facing high costs.

I have used Alteryx for about six months.

Alteryx is very stable. I rate it nine out of ten.

Alteryx is scalable, and I would give it eight out of ten.

I contacted customer support once or twice, and they were quick to respond. I would also rate them nine out of ten.

Positive

Different customers have different data tools like DataStage and Informatica. They also provide good data flow capabilities. Alteryx has a built-in robustness that I was very happy with.

I didn't set it up myself; there was a project manager who set up the whole thing.

Alteryx is expensive. It's beyond the budget of freelancers like me, even though companies usually purchase it for larger projects. There should be a desktop version available at a lower cost for freelancers.

I have used almost all the tools depending on the customer's technological inventory, such as DataStage and Informatica.

Alteryx is a futuristic tool. I recommend negotiating the price before using it. It's a stable tool, and I rate it eight 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.

Primarily, I use Alteryx for Excel. I also use it to automate pipelines whenever necessary.

The most effective feature of the solution is that it is a fast product with good performance compared to traditional solutions. The tool can deal with large or huge datasets.

I think the tool does not run on some operating systems. I think it would be great if Alteryx could provide an in-built machine.

The software is not fully optimized. What I try to do is use Microsoft tools if I have a heavy workflow. I move to a tool to be able to respond to the workflows for a few seconds. I have to wait until I am able to move to another table, and then I can't duplicate. There are too many optimizations to run.

I have been using Alteryx since 2018.

Stability-wise, I rate the solution a nine out of ten. Overall, I have had a good experience. I encountered a few bugs, but I think it is okay because it doesn't happen every day and is normal.

Scalability-wise, I rate the solution an eight out of ten. Currently, the tool also offers a cloud version. Usually, scalability is not needed in my environment. In my company, we only use desktops.

I think that, in my company, I work with the tool as part of a team. Additional departments also use the tool. My team uses Alteryx. A total of ten people use the tool.

The solution's technical support is okay. I posted a few queries and called up the support team for help. I felt that the support team was quick to respond and was also helpful. I rate the technical support a nine out of ten.

Positive

The product's initial setup phase is simple and straightforward.

The solution is deployed on an on-premises model with servers.

If one is a high price, and ten is a low price, I rate the tool's price as a one. The tool is expensive.

I think that apart from Alteryx, I have had experience with a lot of other products, including Sagemaker. I had purchased a product for one of my customers, who then compared it with Alteryx. I also know about some products like Talend and Rapidminer. I didn't like Rapidminer's interface.

I don't use the predictive analytics part in Alteryx.

I am not sure about the data blending part of the tool.

It is easy to integrate and set up the product with other third-party solutions or hardware. The biggest challenge with the integration is probably the need to get approvals and follow up with the organization. I think the process is quite easy.

My company has not had the opportunity to integrate Alteryx with AI tools.

I recommend the tool to others.

I rate the tool a nine 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 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.