Alteryx

I still use SQL, Python, and Excel when I have to - but alteryx has largely replaced all three of these. Every operation I need to do in any of these I can do in alteryx and see what I'm doing each step of the way - so problem solving is also easier.

IMHO KNIME is not user friendly as much as Alteryx. Learning curve is long. Regardless is Open Source, the GUI is awful. To do same job in Alteryx you need to add many components and the configuration is very complex. Although the application is free, the server side is not.
I tried Tableau Prep and as soon as I started to use, I didn't like it. It works only for small data and basic data analytics capability. Even not correct to compare with Alteryx. It is even not Orange and Apple.

Alteryx weighs over Informatica in terms of ease of use and upscaling.

Alteryx may be next to MSBI and Tableau.

IBM is old school, deployment capabilites and automation capabilities lack compared to many market players... Also opensource integrations were limited. Alteryx is good on both deployment and opensource integrations. New versions, IBM WatsonX, is expected to be better the but it was expensive still would be compared to AYX... SAS is old school as well... It takes a SAS team to even install SAS viya properly a few weeks if not months... By this time you would have modeled and deployed the Predictive models and it would already proved their investment...

Microsoft Access is still in place, but will be subsitute by Alteryx, because connection to cloudbased data works, more automazitaion is possible. Easier to use.

We asked our external auditors for suggestions on how to make our processes better and they scheduled a meeting with us and presented Alteryx and then showed us a little bit about PowerBI but it was on their suggestion and their being able to show us at that presentation some clear examples of how we could use it and we were just sold right then. We did look at PowerBI a little but not much.

Overall, I think Alteryx aims for a higher level of user than such data tools as Tableau Desktop or Domo. These two in particular aim to be good at data visualization with analytics as a secondary consideration. It seems to me like Alteryx aims for a more holistic approach that places equal weight on the importance of analytics and data visualization.

Alteryx beats Tableau fair and square. Tableau is good for vizzy but nothing is comparable to Alteryx's data analysis and big data power. KNIME as well is nothing compared to the R&D Alteryx has. Alteryx having a cost compared to KNIME is a factor but the ROI is definitely worth it

The Flaws could be the reason

Alteryx stacks up against its competitors in the marketplace because from day one its goal was to simplify and democratize data processes. Its visual nature and transparent tool set, combined with its highly addictive joy to use make it stand out from the crowd.

The Alteryx interface is easier to use than Tableau Preps. The Alteryx options are easier to find and configure.

Tableau Prep is great too, but my company uses Alteryx. I have no complaints about either.

Alteryx is MUCH more user friendly. both provide the ability to code within them, but Alteryx has much nicer interface. The formula tools have a more simple language that is easier to learn than formulae in SSIS. Alteryx is easy to read with multi colored tools identifying what each one does. It also allows for macros. You can build your own tool to process records of data or batch records together.

Alteryx has interactive visualization capabilities which RapidMiner lacks. Alteryx is more intuitive and suited for enterprises vs. RapidMiner which is more suited for individuals and beginners (since it focuses on the building blocks). Also, Alteryx has a very strong learning community, which makes it easier to learn and utilize in a practical scenario.

We have not utilized any other tools like Alteryx or found any other tools like Alteryx to evaluate them against.

Alteryx low-code/no-code workflow development, and the ability to view my data at every step, immediately improved my development time by at least 60%. Highbond (formerly Galvanize / ACL) relies on a proprietary ACL script coding language, which can be time-consuming to master. Highbond does have a ScriptHub resource, but understanding the coding language can be challenging for less technical users.

Datastage we have used in similar lines but mostly towards ETL implementation

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.

Previous to Alteryx aquiring Trifacta, we looked at it as a possible compliment/replacement. WIth the aquistion, we are looking to the roadmap on full integration and are very excited. Trifacta brings a cloud native solution but currently lacks many of the features/functions that current Alteryx Designer/Server provide.

Knime is also a powerful framework but many organizational specific needs were better served with maintaining our relationship with Alteryx.

Alteryx has many connectors that allow it to bring data in from various systems and export it to various formats and systems (SQL Server, Oracle DB, ODBCs, etc.) There are also additional connectors available provided by third parties that can help with connecting to other platforms not in Alteryx by default. These work well with Alteryx and enable easy access to data that previously took several steps. Excel users will dramatically increase productivity using Alteryx.

Palantir has a much broader scope and is more difficult to use.

Use both and they integrate pretty well. This is mainly because they do different things well. Alteryx allows the user to organize and cleanse the data, while Tableau is much more intuitive in the visualization category. Each has tried to replicate the others strengths, but I feel like the both fall short. Better to use each to for what it does well.

Tableau Prep and Data Guru (Coupa product) are mainly useful in the data prep and blend space. This is useful, but Alteryx provides much more robust analytics potential beyond this in the macro/app space, ML, computer vision, NLP, intelligence suite, prescriptive & predictive space.

It does about as good as a code-free analytics platform such a Tableau, but does not offer as well refined insights through data visualization.