Alteryx Reviews

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.

My company uses Alteryx differently for each of our clients' individual cases.

It has helped across my organization.

Let's say we have a client that has been mostly using Excel for their data preparation, data casing, etc. By using Alteryx, they now spend most of their time in the data prep and then just go to reporting. It saves a lot of time.

I actually like all of their features. But the feature I have found most valuable is the data profiling. I can check the quality of my data and everything else. 

Alteryx is very good - I don't see any room for improvement. I can't think of any downside to Alteryx.

I use a lot of third-party tools with Alteryx. It would be great if Alteryx could take third party tools and incorporate them.

I have been working with Alteryx around two years.

In terms of stability, Alteryx is stable.

It is scalable. We currently have all of our almost 20 employees using Alteryx with plans to expand.

Their technical support is good.

The initial setup was straightforward. Depending on your machine it usually takes less than 20 minutes.

Alteryx is very good. You can do literately anything on Alteryx. Alteryx is so advanced. It's just drag and drop. You don't need to know any coding or other technical stuff to use Alteryx.

On a scale from 1 to 10, where 1 is the worst and 10 is the best, I would rate Alteryx a 10. No doubt, a 10.

We use this solution for self-service data preparation from data warehouses and data marts.

It gives the power back to the end-users. It brings flexibility and accuracy to our new analytics.

The most valuable feature of this solution is data preparation.

Alteryx Connect (data catalog) is also really important for us.

The event handling, such that the file system watcher, is in need of improvement.

Data blending and complex data manipulation and augmentation.

• Fast return on investment
• Increased data analytics productivity.

Workflows and a large number of tools were a quick QA methodology and rapid prototype creation tool.

More emphasis on extensible R and data augmentation interface design.

ETL.

Fast data processing and cleaning.

Crosstab and transpose.

Add inbuilt interactive visualization in Alteryx.

It collects data and manipulation and some Geo-spacial mapping.

It provides opportunities to do some pretty complex tasks easily, without having to worry about the Java. The tools are built-in. You just plug and play, drag and drop, once you understand how to use the tools, it is easy.

I think better visualization would be helpful. In terms of data extraction, during the sequel queries of servers as an example, you can structure your sequel query and it's fine, very readable, but once you run it, it crashes into one complex single line, and makes it very difficult. Then you you almost have to go back to management studio, and run it through management studio and put it through restructuring, and it just seems to me that that's not very user friendly.

It is a very stable solution.

For our purposes, the scalability is fine. But, I think that scaling it for a big enterprise would probably be an expensive endeavor.

I would rate the tech support a 7.5 out of 10.  They do not necessarily provide lots of hands on support themselves, instead they farm it out to partners and forums. 

The learning curve for implementation was a bit steep. You pretty much have to teach yourself as you are setting up the solution. Once you do that, you are OK.

It is a little bit pricey. The desktop version is cheaper, it is on a one year license. And, if you want to do anything on an enterprise name it is quite expensive. The current pricing model may get to be too much in three to four years time.

We also considered DataBricks.

I would advise that you should ask yourself what you need and want, and do a one-month trial.

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.

• Data integration
• Automation
• Data analytics

It saves time on a lot projects.

The analytics are easy.

In the database, it should be more functional and connect to more big data, especially using IPI.