Alteryx has a good UI. We use it frequently in our projects. The tool comes with drag-and-drop features and is easy to understand for business needs. One situation where Alteryx's advanced analytics capabilities were particularly beneficial for us was during a forecasting project. Unlike Python, which requires coding, Alteryx simplifies the process significantly. With Alteryx, users can adjust parameters within the user interface without writing any code. 

Its user interface is one of the tool's best aspects. Once we became familiar with it, we found that tasks can be completed within seconds or minutes, especially for small data analyses. The tool's computation time is also commendable.

We have integrated the product with Tableau and Python. 

Alteryx is a low-code platform, and that's the biggest reason why we chose it. It can also manage a lot of datasets, and everything happens in fractions of seconds. 

Tax returns usually take a day or two for a human to prepare because they involve a lot of data and a lot of checks. But with Alteryx, everything is very fast. It's also easy to develop and deploy solutions on Alteryx.

We used to hire people to just prepare tax returns, and they would work on them for hours. But now everything is happening using Alteryx, so our employees can focus more on the consulting side of tax.

Its most valuable feature lies in its functionality, offering an ETL process similar to a large enterprise with a dedicated IT team. The power of the solution is that it condenses these complex processes into a desktop tool, allowing a single user to handle extensive data extraction, transformation, and loading, even incorporating machine learning. It empowers individuals to execute tasks that typically require an entire IT division, putting this capability at your fingertips.

The drag and drop and layout is simple to understand, with intuitive names of features. For example, to connect native connectors, usually, a fee is required for SAP connectors, however, the tool's flexibility in saving processes and using a vast amount of available memory has been extremely helpful.

The filtering is fast, and it provides a search tool that is great. Macros are useful and fast for reading a lot of files and then creating just one file.

The most valuable feature of Alteryx has been Designer. That has been beneficial because we load our data tables for Tableau. We use Alteryx to load the data into a database from various different data sources to come up with dashboards our business can work with.

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.

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.

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

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.

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.

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.

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

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.

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 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.  

The product's most valuable features include its ease of use for non-technical users and machine learning capabilities. The flexibility to integrate custom code is also an important aspect of the platform for our use case.

Alteryx is user-friendly and allows easy creation of workflows compared to Informatica PowerCenter. The inbuilt functions are good, and it's useful for working with files. You can see the intermediate results in workflows, which is very helpful.

The product's most valuable aspect is its ease of use. It allows me, even as a field person, to create workflows and perform data preparation tasks quickly. Its speed and ability to connect to various data sources in real-time are also significant benefits.

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.

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.

• One-stop shop for data preparation, blending, prediction, and optimization in a single workflow.
• In-database analytics native to SQL Server, Oracle, Teradata, and SAP HANA
• Spatial tools for geographic analysis and data enrichment

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.

Data processing is most valuable. It is one of the fastest data blockers out there in the market, which is a fascinating thing about Alteryx.

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 most valuable feature is user-friendliness, as Alteryx can be used by those without any coding experience or experienced data scientists as it has the functionality to embed R and Python scripts. Alteryx's versatility and ability to graphically present workflows of data are also excellent features.

Alteryx effectively visualizes the flow of data and what happens at each stage. I also like that it's a no-code solution. I also like that you can troubleshoot certain parts of the workflow by putting them in a sandbox.

• 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. 

Overall, I'd have to say the tool is pretty awesome.

The solution offers very good data transformation.

Users are able to read in from any source, combine heterogeneous sources, and providing output or input to the next downstream step. You can put these things together or you can create very complex or simple flows and then tie them together. 

The scheduling within the solution is excellent. 

The initial setup is straightforward.

All of the features are valuable to us.

The data prep and blending are great but so is the machine learning functionality.

We used spatial analysis, which is a good feature.

The solution works efficiently in handling a huge amount of data.

It keeps on upgrading, which is nice. It's always updating with new releases.

A majority of people at our organization like the drag and drop features.

The database is very good.

Overall, the solution as a whole is extremely useful.

The initial setup is easy.

The security on the solution is pretty good.

It has a very nice dashboard.

There are a lot of good customization capabilities.

All of the data science features in terms of unioning and joining data together are valuable. The formula tools are good, and it provides an easy way to summarize data. 

It has some really good, solid, basic reporting functions. 

It's not as robust as a lot of the dynamic interactive tools, but it certainly gets into the more static reporting very effectively.

The ease of use is the solution's most valuable feature. It doesn't require coding for usage. I only have to drop and drag the available options to perform complicated functions.

The most valuable feature of Alteryx is its performance. It is a powerful solution.

It is efficient in optimizing our ability to get information.

The solution has excellent drag and drop functionality. There's no need for coding. There are nodes ready for us to use as well. It makes everything extremely easy. The user-friendliness is a big draw for us.

Geo features have made spatial mapping large retail universes possible. The basic package of manipulation tools are the tools that my team use the most. It makes lengthy Excel processes seamless and lighting quick in comparison.

It has everything that one needs. Whatever you want to do with the data can be done with Alteryx. However, we haven't implemented it on a large scale because we don't have a physical server. We have a virtual server for this, and there are limitations to that. So, we use it for smaller data chunks, not bigger data volumes. It is mostly for files, not for databases.

The most valuable feature of Alteryx is the intelligence suite. 

The analytics are easy.

One of the most valuable features to me is its ability to take millions of rows of data, blend them with more millions of rows of data, then output the data set to a Tableau Data Extract (*.tde), which I would then use to build a dashboard in Tableau.

Another of its most valuable features gives me the ability to pipe external data onto a server in a temporary table. This frees my 16GB machine up while the server does all the heavy lifting. Blending data this way is faster, as a simple blend of a couple of million rows can take a minute or two. Also, because Alteryx can output to a *.tde, we are able to use it hand-in-hand with Tableau Server to develop data access solutions for our users.

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.

The most valuable feature of Alteryx is user-friendliness.

There's no single feature I can think of that stands out as being the most valuable, but we've worked on multiple areas such as analytical apps, especially to connect with Facebook, LinkedIn, and multiple other online data APIs. We also use batch macros to automate and repeat steps many times over. These two features help us a lot. They are slightly more advanced, so it's not for a regular user, but these are the areas where people ask for assistance.

Alteryx is a simple and easy-to-use solution.

The modelling features are very good in Alteryx and better than what you'd find in open-source software. Python and R rule the market. Although Alteryx is a paid software, it is equally able to provide better performance without writing a single line of code. That's the USP of the software as such. It's very user friendly. 

The feature that I have found most valuable for Alteryx is its geo-referencing feature, it is very good. I use it a lot, especially for supply chain. For finance, we have data landing which we look at a lot. There are models to help improve matching data and more realistic intuition on the data we have.

It is very easy. It is very straightforward. Sometimes you need a bit of help, but it's more like it fixes itself. So if you are used to handling data, it should be very, very easy.

The connection feature is quite useful to our organization. We connect with other databases. We connect with Microsoft SQL databases or with Oracle databases, and we connect with SharePoint lists, and we can connect with Outlook email servers as well.

The stability is very good. It hasn't given us any issues.

The scalability has been great.

Technical support is very helpful.

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.

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

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

The three data signs and data engineering are great features.

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.

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.

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 connectors are a very good feature and Alteryx can connect to a lot of data sources and there are a lot of options. We can use the ready-made models in the solution for advanced analytics, and we can also include our custom scripts. It gives a lot of flexibility and there are a lot of characters that are available. It's a very user friendly product. 

I like the fact that you can easily blend data from different platforms. That is one nice feature.

Additional comment: You can connect multiple input tools to different platforms and use joins/union to either concatenate or blend data in a seamless fashion.

I think the most valuable feature is the ease of use for my business scientists. They do not need to be experts in R and Python coding, and they can do their complete analysis projects without knowing the code. I think that one of the biggest reasons we are depending on Alteryx.  

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

Crosstab and transpose.

The drag-and-drop capability to create a workflow works like drawing a flow chart. Each icon represents an action. You drag the action on the canvas and connect it to the data source, make configurations on the action, then run the workflow. When data goes through the process, the action will execute and you get what you want afterwards. The actions are intuitive and you can design you own way to do the same thing.

The philosophy of the citizen data scientist is the key piece, which means the no-code analytics capability. This is the feature that attracted us the most.

The data preparation. We have high reporting needs and the data is stored in many different tools. We are moving to predictive analysis too. Still, we need an easy to deploy solution until the IT department finds a better solution to connect all data sources.

The drag-and-drop functionality, the ready-to-use analytics module, and the ability to track my data pipelines visually are the solution's most valuable features.

The Alteryx designer has been the most useful feature in the solution.

The UX (user experience) is quite good on this solution. The UI (user interface) is also excellent.

The solution has a very strong community that is involved in the product. It helps make the usage easier and helps us find answers to our questions.

Alteryx integrates well. The most valuable feature for me is integration.

I can read data from a database on the web and import it into my Alteryx database.

It is very easy to use. 

It's quite user-friendly, which I enjoy.

The GUI is simple and it integrates with Python.

The most valuable feature of this solution is data preparation.

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

Data Blending and Predictive Analytics: Alteryx is very intuitive and you don’t need to know how to write code to use Alteryx.

The solution does a good job with data transformation. We're using it for our business modeling.

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. 

The scheduling feature for the automation is excellent. The machine learning suite has been pretty useful in terms of building models. I've been exploring it for a while. The in-database tools are extremely useful as well.

The interfaces are perfect.

The solution is easy to set up.

The stability is quite good. 

We have found that the scalability is good and very easy to handle.

The design portion of this tool is easy to use without code, which his something that something we can appreciate. We can say it's code-free usage.

It's super easy to learn how to use it — the learning curve is very small.

• Data blending
• Calculations
• Predictive models, which are easy to use, and help a lot with fast design and deployment.