Alteryx Reviews

Alteryx is typically used for data preparation and blending. I have clients who use it for Special Analytics as well as Churn Analytics.

Everything was manual and repetitive. With Alteryx, instead of spending three hours preparing the reports, it will only take them two minutes because everything is connected to the database.

The drag-and-drop features are useful for data scientists who do not like to code because it is already in the system.

Alteryx has good prep and blend features, as well as the ability to connect to various sources.

My understanding is that they will include a visualization feature. 

All of the reports are migrated or exported in an Excel file, and most of the time, a business intelligence tool is required.

They could have better reporting. The aesthetic could be improved.

We have limitations on the number of fields. It doesn't really get everything if we have to add more columns.

I have been working with Alteryx for four years.

We are working with the latest version.

We're working on both the design and the server version on-premise.

So far Alteryx has been stable.

Alteryx is scalable. If you use the server, you simply add to the specifications based on the size of the data.

I have not contacted Technical Support. I have a team of Alteryx experts, so we don't rely on other support.

We are also working with the Designer Platforms for four years. It includes the Data Science features.

We were working with the most recent version.

I am familiar with many solutions.

The initial setup is fine. 

Prebuilt connectors are available, and you may need to create middleware, particularly for SharePoint. Most clients have it in either SharePoint or GoDrive which doesn't have a direct connector, we will have to create another one.

As long as you are connected to the source countryside, the tool itself doesn't require any special maintenance.

I have a lot of business use cases where the ROI is less than a year, and sometimes even in three months.

The designer version has a list price of $5,995 USD. The server version is even more expensive because it is only for collaboration. The designer license is needed to access the servers for collaboration, which in my opinion is expensive.

We were an Alteryx partner.

In terms of Alteryx, we resell the solution to our clients. I do have a team that handles the implementation. I specifically look for clients and see if there are any other excuse use cases that we can do with them.

Be aware of it, there are several versions, and there is a free trial that they can use. Once they understand how to do everything you're doing in the system, it's very simple to transfer it to Alteryx.

I would rate Alteryx an eight out of ten.

The solution is primarily used for data preparation, data cleansing, and, in some cases, predictive analytics. That said, the major use is in the preparation of data.

I am the sales guy. I don't work with the product every day. However, I hear from my customers that they like the easy-to-use interface. Another feature they like is the in-database feature, and, right now, the new intelligence suite add-on they delivered a couple of years ago.

The support is very good.

The principal problem is the pricing. They're expensive products. They don't have an option to scale the product while the customer is starting to use the product. There are no options for customers that want to move from smaller scale and expand the solution to the rest oth the organización. The Designer (pleople who develope models and flows) cost 5,195 USD each one, but if you want to collaborate, you have to buy a server which cost 80,000 USD not matter how many users you have, so you cannot scale from a small group of users to a large one.

It's only available as an on-premises solution.

It would be ideal if the product offered some sot of option for smaller companies.

The solution is hard to scale in that it is pricey. You need to buy a server. You would need to have the correct sizing, and, if you don't, you would need to buy a bigger server, which is expensive. They don't have a way to grow the product progressively, in a progressive way.

The support is very good overall. We are satisfied with their level of service. They are knowledgeable and responsive. 

We also use Dataiku. We are partners for both products.

In the case of Dataiku, they have a stacking in Amazon. We are offering this option right now. I know that they are going to deliver an option in Google Cloud also. Alteryx, on the other hand, is only on-premises.

The licensing model that they use makes it a very expensive proposition for many companies. It requires buying a server, as it is only on-premises. 

In order to have designers, and, if you want to collaborate, you have to buy a server. If the designer is $5,000, and if you want a server, you have to pay $80,000.

I've been searching about the difference between both Dataiku and Alteryx products. I'm working to evaluate the two and compare them to each other. Technically, we have a customer who is comparing both products, so we have to prepare a document comparing them for that purpose.

We are Alteryx partners.

I'd rate the solution at an eight out of ten. It's a very good product, however, the pricing makes it quite expensive.

In comparison, I love Dataiku. I've seen it's a very, very good product and we are working hard to start offering this product to all our customers. They have an option for companies to from medium-size to large-size. However, they don't have options for small customers. That said, you can start from, for example, an investment in $30,000 and up. You can go progressively investing in the product. That's not the case for Alteryx.

I am the head of investigation on-site, I use the solution every day for merging and other management of records. I also export data to individuals that need the information we store, such as facilitators.

The solution allows us to manage our databases data.

I think the most valuable feature for Alteryx in a health facility is that it permits cleaning, organizing, and merging of databases such as Excel and Access. This is very valuable for us since we have many databases.

The interface could be improved. Currently, when you are looking at the information on the screen it is broken down into three parts of the screen. For example, when doing algorithms and you want to see the results on the screen this is when it gets really difficult to view. However, this is fine visually to work with on a big screen but when you are working with a laptop screen it is not very comfortable. Everything is very small.

You have to know to use it. You have to have some training and it's hard. This could improve.

I have been using the solution for approximately 10 months.

I have not had any issue with the stability of the solution.

Since I only have one license to use the solution it is difficult to know about the potential scalability.

The setup is really easy.

The install took approximately 35 minutes.

The license is really expensive, we cannot afford to have two or three. It takes away all the budget of my area.

I would recommend the solution 100%. I really think it is a better platform than competitors.

I rate Alteryx a nine out of ten.

Our primary use case for the solution is merging multiple data tests and utilizing various data sources.

The solution has improved our organization by enhancing the speed by which we can pull data.

It is efficient in optimizing our ability to get information.

The solution can be made more affordable.

We have been using the solution for approximately two years.

The solution is stable. I rate them a ten out of ten.

The solution is scalable. However, based on the price, it can be pretty costly, and organizations tend to limit the availability of that software to its users.

We have not had any experience with customer service and support.

The initial setup is straightforward.

I rate the solution a ten out of ten. The solution is good but can be more affordable. On the other hand, it is a great tool because of the community and can integrate various tools, data and types and software.

We have multiple use cases, but the most typical use case is to clean the data and use it for reporting.

The data transformation feature is the most valuable. The ability to ingest data, visualize data, and transform that data is useful.

Sometimes, there are performance constraints. Especially when a large file has to be ingested, the system slows down a bit. Its performance is the only thing that can be improved.

I have been using this solution for just two years.

I would rate it an eight out of ten in terms of stability.

It's able to scale. We currently have a lot of users who use this solution.

We had a good experience with them. We are happy. I would rate them a four out of five.

Positive

It's simple.

We did it on our own.

It has a good price.

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

We primarily use the solution for basic data analysis and forecasting.

The giga size is very good. 

The solution offers excellent predicting power. The accuracy and confidence have been great.

You don't have to be tech-savvy or technical to use the solution. There's a lot of drag-and-drop functionality.

The visualization could be improved, as could the BID bots.

The solution could work on the BI side of the tool to make it a bit better.

I've been working with the solution for five or six months.

I've liked working with Alteryx so far.

The solution is totally scalable. Users can work with the data at all levels and determine if you want to scale it. You just have to choose the product model with the larger amount of data.

The technical support is very good.

I've worked with other solutions such as Knime, among others, however, in a corporate environment, I've only worked with Alteryx.

The initial setup is very straightforward. You just need to go through the manual. Reading it makes everything easy.

Each deployment is different. Some jobs seem easy, but then the back end is complex. Other times it can be deployed in practically one click. It all depends on the customer requirements.

We're Alteryx partners. We handle various deployment models, depending on the client's needs.

I've worked with other solutions such as Knime, among other tools for data science and data prep. It's great that this solution is just drag and drop and easy.

I'd recommend the solution. I'd rate it 9.5 out of ten.

I implemented Alteryx for a logistics company. 

It helps clean messy data and provides spatial analysis.

We create workflows to automate central reporting and visualize data directly in Tableau. 

We use Alteryx everyday. Using the product, we earn a lot of time, which is used to do other tasks.

Multicategories exist in Alteryx: These categories are flexible and answer a lot of controlling rules.

• Alteryx could be improved in the area of analytics and central governance. 
• The next feature release should include easier reporting. 
• Improvement in the coexistence of In-Database, Python and R tools.

We primarily use the solution for automation, data cleansing, QA, some data science and machine learning software for the company.

The product's Macros probably are one of the most useful aspects. It's obviously useful overall if you just combine all the tools, however, in terms of usability, the Macros really stand out. 

Using the Alteryx scheduler, and the use of Rtools for machine learning is very helpful.

These are all a bit more advanced, in terms of tools, however, they make for a very good user experience.

We've had a lot of issues within the Alteryx Server. It really could be improved.

There are memory management issues in terms of the Mongo database that they manage. There could be a better user interface for the gallery, which is where we automate the workflows. 

Sometimes workflows tend to queue up, and they tend to get canceled for some reason that we don't know sometimes. 

I've been using the solution for five years at this point.

The stability is okay. It's good on the designer, however, it could be better on the server.

In terms of scalability, the server is quite scalable, however, the designer is not.

The initial setup was easy, overall. It's easy to use and easy to learn and you don't have to be a data scientist or an engineer to use it. It makes the setup very straightforward, as the overall design is very approachable.

The deployment likely took us about two to three months to set up. It was five years ago now, and therefore it's difficult to recall.

We mostly handled the initial setup ourselves. We didn't hire consultants or integrators.

We're just a customer and end-user. We don't have a business relationship with the company.

We have an Alteryx server, and we also use the desktop version or the designer version on our workspaces, which are hosted on the cloud.

In general, I would rate the solution at an eight out of ten. We've been mostly happy with it, however, there are areas in which is could improve.