Alteryx

Alteryx has been a game changer for our organization. It allows us to work with multiple large files at once that are in various formats, with the ability to merge files, run calculations, add additional variables, etc. It's great for automating tasks such as running reports where you're taking data from multiple files that are in different formats and combining them into one file with everything in the same format. Once you have your workflow built out, it's simply a matter of swapping out the input and output files and clicking "Run." It's also great for working with files that are extremely large that otherwise might slow your computer down or cause it to crash.

Alteryx is very powerful, and the preferred data processing engine for refreshing.

Alteryx is best suited for data quality inspection, data cleaning/engineering processes, and statistical calculations

I can interface with SharePoint using APIs in Alteryx. It is also great for automation.

Alteryx is perfect if you find yourself repeatedly doing tasks. Alteryx can be used to automate these, and you don't need to understand a coding language like Python, the low barrier to entry really helps with this.

If you ever find that the tools in Alteryx do ALMOST what you need but you need them to be more dynamic for automation, you've got a whole toolset in Alteryx to help with this. Macros in Alteryx, and the interface tools, allow users to drill deeper into Alteryx to add the extra customisability when needed.

Well suited for predictive analytics, machine learning, and data analytics-based assignments where we leverage their intelligence suites. Also, its analytics cloud offering allows easy processing of workflows in the cloud, along with scheduling and management options. Less appropriate as a standalone visualization tool as it is quite inferior in that respect to a Power BI or a Tableau.

Useful when attempting to automate a process that is done manually, as long as the process/steps can be defined logically. It’s saved me huge amounts of time when collating information from numerous files into a single report, which is very easy to set up and runs extremely quickly. It’s also helpful when several different reports need to be created in one go, e.g. an Excel file for each country - it just takes the click of a single button to generate all those files, it’s like magic. Less useful when users need to interact with the data to review/interpret it - a dashboarding tool such as BI/Tableau may be required for that, but Alteryx can still be useful for preparing the data that feeds into it.

Doing some spatial analysis like trading areas. Cleaning data to make it more reliable and usable for visualization purposes.

Alteryx is a great tool for transforming any data source at any skill level of the user. Little to no programming experience is required in order to build and automate some amazing processes that have no business remaining manual. If you happen to work for a company that has precise ETL and never need to transform your data beyond how it already is in database tables or data marts then you may get by without needing Alteryx for data cleansing and prep but there is still so much other functionality Alteryx has to offer even if you have the cleanest databases to work with. Alteryx can't quite replace BI tools such as Tableau or Power BI in terms of having a dashboard that folks can navigate to and interact with but it is a great tool for preparing your data for BI tools or even replacing SSRS.

Data wrangling / Data prep: The Alteryx low-code/no-code workflow development environment immediately improved my coding efficiency by 60% or 70%. The ability to view my data at each individual transformation step is unparalleled.

Quick results: initial Alteryx workflow development has a very low learning curve. I was able to quickly get up-to-speed using the free online training resources.

Macros and server use can be challenging. But those are advanced topics.

In a technical eco system where you have a blend of both legacy and digital technologies Alteryx helps you to deal with data easily and analyze it…may not be good option to use it as an ETL tool

To any "Excel power-user kind of" profile, to any any data owner willing to reap information from huge volumes of data and facing data prep difficulties, I would definitely recommend Alteryx. Yet, Alteryx is not the best suited for machine learning, even in a low-code approach and should for such needs be regarded as a very useful preparation tool before actual machine learning processes. Alteryx deploys well bottom up, pushed by thrilled users and doers. It is not to be launched as an ERP-like project from top down, with armies of consultants and project managers.

Alteryx is best suited for organizations to handle data distributely, meaning even a "normal" member can perform the data processing at his needs with knowing complex or difficult coding skills. In some cases, such as the data is not well structured, Alteryx might encounter challeges.

Well Suited

• Enable self service data to information insights in a no/low code environment
• Enable Line of Business knowledge to flourish
• Speed to insight for teams without dedicated analytics/technology experts

Less Appropriate

• Medium/Large organizations without a strong ability to support user base and govern useage patterns
• Medium/Large organization without a history of data governance/quality sucess and stabilty
• Medium/Large organizations without strong self service mindset in both IT and Alteryx Users

Alteryx is easy to use to wrangle data from multiple sources and combine into one stream. Tools allow non-sequel writers to create workflows in minutes to perform quick analysis of data. The ability to turn areas of your workflow on and off to test different scenarios within a workflow is one of the best features for me.

In my organization, we regularly create workbooks and duplicate workbooks to show various versions of analyses. This creates a lot of redundant files and can oftentimes break links in workbooks and lead to manual errors being performed. Alteryx prevents all of this by allowing users to create automated workflows that perform the same - or dynamic, if needed - tasks that users might perform on a regular basis.

Alteryx is very flexible if you are using the right tools within it. It is well suited for dealing with data files that need to be joined together or analyzed. It is less appropriate for working with files needing OCR conversion to retrieve data until those files have been read by an OCR software.

Best suited in large organizations that are looking to scale analytics. In my opinion, Alteryx shines when it's leveraged with Alteryx Server, allowing users to share workflows more easily, create analytic apps, and schedule. I'm personally responsible for enabling the company to perform self-service analytics. Alteryx is a great tool for that, and once the users understand how to use it, they love it. Furthermore, we need to track ROI because, well - it's an expensive tool, and we need to ensure we're getting value for the license costs. It's fairly easy to track the hours we're saving on a regular basis once we've automated a process.

Automates manual excel work very well. Transforms manual requests into automated end user-initiated reporting. It brings a lot of the work that IT usually needs to deal with down to the analyst level, saving those resources for high code jobs. Light weight enough for no-code users but has the python and R capabilities.

Alteryz is well suited for solving almost any type of business problem, or problem in general, that requires data. To some extent, the sky is the limit, and Alteryx continually enhances its capabilities in things like NLP, computer vision, ML models, etc. While it does have some data visualization capabilities, it is not extremely well suited in that regard, though at the moment it isn't trying to compete with the likes of PowerBI or Tableau. Alteryz works well with such software specializing in data visualization.

Alteryx could be very useful if you need to combine data from multiple data sources. Also, it would help data preparation and cleaning before analyzing data. If the data quality is already excellent, then it would probably be less useful.

Alteryx Analytics is suitable for less technical users who do not have coding experience, you can gather information rather painlessly; however, it is still not quite as good as using a language such as Python or R to integrate your advanced analytics work.

I regularly recommend Alteryx for solving a variety of data reporting issues. The only reason it doesn't get more mileage in our group is that data analytics is a side project for me, rather than my full-time role. If you need to regularly revise a spreadsheet in the same way, it can trim the time from hours to a single button click. The workflow I currently use each day involves Alteryx analyzing and displaying trends over years with detail that drills down to the day. It has to read and write just under 2000 files at this point to do that and accomplishes that within about 6 minutes after I click the Run button. If my computer were faster, it would take even less time. The only situations I haven't been impressed with Alteryx for have been in presenting data. If you want a pretty output, just use Power BI afterward though.

Alteryx is a well-rounded platform suitable for all functions from ETL, data cleansing and wrangling, analyzing, reporting, and even data science functions. Alteryx used to fall behind in cloud capabilities, but in the last year it has stepped up its game in that area as well with a Snowflake partnership. I'm not sure there are many scenarios where Alteryx should not be used!

Pulling data from databases and preparing for data visualization is our primary use for Alteryx, however if you have perfect data, Alteryx can get redundant, but honestly who has that.