Alteryx Reviews

We utilize Alteryx for the purpose of transforming data to generate a report for data analysis that predicts the number of customers who will upgrade or downgrade within a specified time frame. After creating the workflow and building a dashboard on it, we set it up on a client-server to run live. When new product data is introduced, we fetch it directly from the database. This process is based on Microsoft SharePoint, and we have specific nodes for this purpose. With the appropriate access, the node will extract the data from Microsoft SharePoint and transform it into the desired format, which we then use to build KPIs and dashboards.

The most valuable feature of Alteryx is its stand-alone version that we do not have to download dependencies for loads. Additionally, the scan is useful for beginners.

Handling a set of data sets for building, cleaning, and preparing is a straightforward process.

The price of the solution could improve by being lower.

I have been using Alteryx for approximately two years.

Alteryx is a stable solution.

I have used Knime previously.

We use the free version of the solution. There are enterprise licenses available. It cost approximately $5,000 annually. It is an expensive solution and there are additional features that cost more money.

In today's world, where every field deals with data, it is essential to have tools that enable us to manipulate, clean, transform, and build dashboards from data. Traditionally, Python and other programming languages were used for data preparation, but now with Alteryx Online, even individuals without coding experience can enter the field and provide valuable solutions to clients. This makes it a useful tool for anyone who needs to work with data.

I rate Alteryx a nine out of ten.

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.  

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.

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 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. 

We have our data in several ACP-based systems, so we rely on Alteryx to extract the data from the system and build the data modeling in Alteryx. There isn't a cloud version. It is on-prem, but we can deploy it on the cloud, too. We do on-prem development and deploy it on the cloud. 

Alteryx's connectivity is essential. We like the ability to connect the solution to multiple sources. It's easier than other data modeling and extraction solutions. It's built on a self-service concept, so it's easy for anyone to open the tool and directly import or export data from it.

It would be nice if they can provide Alteryx with more options for In-DB connectivity. That functionality is there, but it doesn't include all software we are connecting.

In-DB is a concept in Alteryx where we don't need to export data into the Alteryx server to process. The data remains in the source system, so Alteryx can directly manipulate it. That feature is available only for a few tools with limited options. 

I've been using Alteryx for about two years now.

Alteryx is stable. 

Alteryx is scalable. My teammates and everyone in my company have an enterprise account, so we are able to access it.

Alteryx support responds quickly, and my interactions with them have been good. 
I rate Alteryx nine out of 10.

Setting up Alteryx is straightforward.

I rate Alteryx nine out of 10. I have worked on multiple media tools. This one seems to work for most use cases, and it is pretty fast when compared to others. 

If you're implementing Alteryx, you should get the Alteryx application and take advantage of the self-study materials available in their portal. It'll be easier if you try out this application before you start working on the toor.

We used the solution to design our models and databases, and then we used it to automate it through Excel.

The fact that it can turn up all the functions that Excel takes hours to do in a faster way is a very valuable feature. Inputting from various sources is easy. The fact that it can filter or do other kinds of inputs is very useful for Alteryx. Also, the thing with Excel, as opposed to Alteryx, is that Excel can only take up to a number of rows, and after that, it freezes. In my previous work experience, I had to deal with 10,000 or even more rows. Excel was not feasible at all as opposed to Alteryx, which just automated tasks and gave us the results in a few minutes. The reliability was much better.

The initial setup is easy.

I have not yet been exposed to Alteryx as much to comment on negative experiences. I'm taking a class this semester that has to do with Alteryx. I'm pretty sure that once I'm learning the projects and utilizing Alteryx more, then I can give back more feedback.

The usability could use some improvements. There are icons that you choose in terms of inputting the tool or even for filtering and then running different functions, there are different ways of designing your input tools and output tools, and that could get confusing.

I would suggest that if there's any way of simplifying it so that instead of tools or instead of understanding how it works, we could focus more on its usability and the output of it. For me, it was a bit challenging to figure out how to work with Alteryx. If there is any way to make the learning curve less steep, that would be ideal. 

I've used the solution for a year and a half. 

The stability is good, and, unlike Excel, it can handle large amounts of data and not freeze. 

There have been actually hiccups and issues with Alteryx, however, to deal with that, what we did was we went back and saw what the issue was, and mainly the issue was due to Excel. Maybe the value, function time, or strength value was not supporting it. We had to edit many functions and strengths to rerun it through Alteryx. That's one thing that's good in Alteryx: if we run and it's not working, it gives us an output and tells us where we are going wrong so that we can go back and troubleshoot on the problematic areas.

I haven't had a chance to deal with the tech support due to the fact that mostly whenever things went wrong with Alteryx, we were able to fix it by ourselves or with the engineering team. Engineering was able to troubleshoot it and fix it by looking at the output given by Alteryx in the email. It tells you where things are going wrong. For that reason, we did not have the opportunity to go and ask for advice from support.

I have had experience in automating projects in Excel and Alteryx, among others.

I have more experience in Alteryx itself than in Designer. A lot of databases were modeled, and we went and changed or updated the models, attributes, and entities. Then, what we did is we created them in Excel and we just auto-run it whenever we needed to.

It's not complex, and it's also not straightforward. It depends on which database and how many functions you are using or how much you are designing through Alteryx. If there are a lot of structures and if there are a lot of values that you're doing through Alteryx, then it would be hard. That said, from my experience, it's actually not that tough.

I don't deal with licensing. I can't speak to the exact cost of the solution. 

At first, you need to know the capabilities of Alteryx. It's a good idea to attend a lot of webinars or do a project. That would be really helpful to understand how powerful Alteryx is. Alteryx is used a lot in financial industries, according to what I have seen. It becomes really taxing to do everything in Excel or spreadsheets. Something that would take an hour or two hours to do it manually can take five to 10 minutes for Alteryx. Therefore, try a small project or understand the intricacies of Alteryx and that will get you started.

I'd rate it seven out of ten.

• Data acquisition, accessing all types of data services no matter the format, vendor or platform, I can connect, read and process the data.

• Data blending and descriptive, creating consolidated data sets, such as joins, unions, summarize, and all basic and advanced data manipulation tasks. 

• Advanced analytics, like predictive and prescriptive analysis, which are very good tools. 
• Preparation

It involves reading multiple data sources, in different formats, reshaping and blending them together to answer business questions. We generate models for predictions and optimization.

Alteryx speeds up the time to obtain business answers/insights on data. It can quickly process huge amounts of data. It allows you to have your business prepare their own data sets, and it can even be used by IT people. The speed of processing is impressive to get something in minutes that would normally take you a couple of days or weeks.

Shortens the time required to start analyzing data and looking for insights, minimizing the tasks that do not add value to the business and maximizing the analysis phase. 

• The codeless concept and speed of processing are unique. Super intuitive to use and easy to master. No coder needed.
• I did not find a data source that I could not connect to yet.
• In/out, preparation, blending, parsing, and transformation tools are the fundamental ones to start analysis.
• Spatial operations and analytics are super powerful for analysis which requires these types of models/operations. 

Even when it already includes some AI models, this area could be improved.

Another area which could be improved is the visualizations. It would be great to create the final users' visualization within Alteryx.

Finally, the UI does not reflects the amazing tool Alteryx is.

Three to five years.

It is absolutely stable. It has not crashed. It takes seconds to process huge amounts of data without too many resources on the machine.

There are no scalability issues. It is enterprise ready, and can multiple your processing power.

It is one of the most complete and great customer service that I experienced with a software company/ecosystem.

The customer support is fast, complete and proficient. The partner ecosystem is extensive, and all have a couple of very advanced resources to provide support.

Finally, Alteryx has an online community (Check it out at http://community.alteryx.com ), with a lot of people willing to help users.

I used several ETL tools, but none had the scope of Alteryx nor the ability to perform the analysis itself.

The initial setup was very straightforward using a wizard.

Next, Next, Next, OK process. Super easy, intuitive, and problem-free.

Both vendor team and in-house. In all cases, it was a straightforward experience. The vendor was very proficient and Alteryx always had our backs.

ROI is huge. There are some secondary benefits, like analysts getting their post 5 PM time back or the ability to shorten all closing processes to a half or less.

Opt for the three year subscription. It is 20% less than the yearly one.

It is $4,000 a year, so it is cheap versus other solutions. It also accomplishes three times the volume on the job in the same time (as the other solutions).

I evaluated Datawatch and QlikView. 

Datawatch: Performance was not great and it was not so straightforward to implement.

Download the trial and test it. You will be amazed. It is the complete package for people who work with data.

Most important criteria when selecting a vendor: 

• Provide a good product.
• Have good support.
• Needs a clear vision of the future with a very solid roadmap.