Likelihood to Recommend
Well Suited Scenarios
Data Preparation and Integration: Alteryx excels in data preparation tasks, such as data cleansing, transformation, and integration. Predictive Analytics and Modeling : It enables users to perform complex statistical analysis and models and algorithms, making it more valuable for cases like customer segmentation, demand forecasting, fraud detection. Automation WorkFlows: Amazing for repetitive data processing task, or automated rescheduling.
Less Appropriate Scenarios:
Real Time data processing, large scale big data processing, Heavy statistical computations. Read full review
Dataiku DSS is very well suited to handle large datasets and projects which requires a huge team to deliver results. This allows users to collaborate with each other while working on individual tasks. The workflow is easily streamlined and every action is backed up, allowing users to revert to specific tasks whenever required. While Dataiku DSS works seamlessly with all types of projects dealing with structured datasets, I haven't come across projects using Dataiku dealing with images/audio signals. But a workaround would be to store the images as vectors and perform the necessary tasks.
Read full review Pros Pulling data from multiple disparate data sources. Allows users to see the data at every step of the workflow to be able to cleanse, analyze, and optimize the data. Provides an analytics platform that is easy for users of all levels to thrive in whether they are just starting out in their analytics journey or they have a master's degree in Data Science. Read full review The intuitiveness of this tool is very good. Click or Code - If you are a coder, you can code. If you are a manager, you can wrangle with data with visuals The way you can control things, the set of APIs gives a lot of flexibility to a developer. Read full review Cons A larger library of data sources being leveraged/licensed through Alteryx directly similar to the Experian and Dun & Bradstreet data that is available now would be ideal for additional data enrichment. The ability to take R and Python-based data insights/model outputs/forecasts/etc. and pull directly into downstream tools and reporting is a bit lacking and could use improvement. Read full review Read full review Likelihood to Renew
We've developed a working partnership with Alteryx. As an enablement suite, we're continuing to innovate and deliver great products with use of Alteryx in our solutions. Alteryx use expands to our global product development teams and is in use in multiple parts of our organization. Alteryx also delivers Experian demographic content to other clients in their product offering. We're highly likely to renew, but that decision is way above my pay grade.
Read full review Usability
I've found that while some things might take a little longer to create, the flexibility of Alteryx allows you to perform any function needed. I haven't found a use that was not available in Alteryx yet. APIs and XMLs can be created to perform certain functions. In addition, CMD line commands can be sent using Alteryx to perform certain functions as well.
Read full review
As I have described earlier, the intuitiveness of this tool makes it great as well as the variety of users that can use this tool. Also, the plugins available in their repository provide solutions to various data science problems.
Read full review Reliability and Availability
I use many programs and compared to others, Alteryx virtually never goes down, freezes up or gives an application error. Over a 4 year time period that I have used this program, any of these may have happened 3 times. It is an incredibly stable program that I feel completely confident in.
Read full review Performance
I have not complaints with the system. there are after events that can be added to flows that send emails with a stack trace for visibility into any errors. Stack traces include Tool IDs at the failure point to help debug. Overall the flows run quickly and once I work my own bugs out they are reliable
Read full review Support Rating
Stellar, bar-none. Some of the best support folks of any vendor. The Alteryx Community is the most responsive and supportive. On the rare occasion of a release issue or bug, we've been able to get quick help to solve the core problem. Alteryx does not play the blame game. They genuinely help the users solve their issues or respond to questions
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The support team is very helpful, and even when we discover the missing features, after providing enough rational reasons and requirements, they put into it their development pipeline for the future release.
Read full review Implementation Rating
There is really not much to it (the installation, that is). Once you get it installed, along with any of the add-ons (demographics, R, etc.), you are up and running almost immediately. There is really no additional setup. You can immediately begin blending data, running demographics, performing spatial queries, running predictive analysis, etc. And for many of these functions, the learning curve is quite easy.
Read full review Alternatives Considered
Knime is open source and free. It also positions itself a little on machine learning. But the user experience and the features available are far less powerful than Alteryx. I was a former user of Lavastorm (ancestor of Infogix Data360) and got acquainted with the low-code graphical approach thanks to this tool. RapidMiner is the Alteryx for machine learning, but is not at all as tooled as Alteryx for data prep. I also like to use Orange BioLab which is really for machine learning and offers an excellent low-code/graphical user experience... on top of being free.
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Strictly for Data Science operations,
can be considered as a subset of Dataiku DSS. While
supports Python and R programming languages, Dataiku also provides this facility, but also provides GUI to creates models with just a click of a button. This provides the flexibility to users who do not wish to alter the model hyperparameters in greater depths. Writing codes to extract meaningful data is time consuming compared to Dataiku's ability to perform feature engineering and data transformation through click of a button.
Read full review Scalability
Individual analysts can quickly generate results using their own copy of Alteryx Designer. But using the Server and developing macros for more complex needs can be time consuming.
Read full review Return on Investment Error handling - allows controls to be built into workflows easily and allows them to be isolated and spat into control reports that can be easily reviewed and audited, thanks to the ability to create multiple outputs in one go. Time-saving - saved huge amounts of time, especially when moving Excel processes into Alteryx. Product development - allowed my firm to create products that we have been able to market and sell to clients. Read full review Given its open source status, only cost is the learning curve, which is minimal compared to time savings for data exploration. Platform also ease tracking of data processing workflow, unlike Excel. Build-in data visualizations covers many use cases with minimal customization; time saver. Read full review ScreenShots