Alteryx aims to be the launchpad for automation breakthroughs. Be it for personal growth, achieving transformative digital outcomes, or rapid innovation, Alteryx converges analytics, data science and process automation to enable users across organizations to make business-altering breakthroughs. Alteryx Designer can be used to automate every analytics step — from data prep to data science. Access any data source or type, then blend via drag-and-drop interface.…
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Posit
Score 9.1 out of 10
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Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
RStudio is great tool with cross language integration with minimal changes. RStudio support team is very prompt and informative. Simple installation setup.
At this point we have more analysts that are enthusiastic about Alteryx than R across the organization but more expert users in R than Alteryx. We have had challenges deploying apps in Alteryx so at this point RStudio is our platform of choice for deploying apps to our internal …
We're trying right now to get more people using it at our company so we can send management documented cases for how we can expand and purchase Alteryx Server which will extend the capabilities even more and across more departments. It's been well suited for pretty much everything we do on a repeating schedule. It's worth the time to set up the workflows. When Treasury sends me the bank download now - I save it to a folder and run our workflows and send back 2 journal entries in .9 seconds. (yes - in less than a second it's finished running)
In my humble opinion, if you are working on something related to Statistics, RStudio is your go-to tool. But if you are looking for something in Machine Learning, look out for Python. The beauty is that there are packages now by which you can write Python/SQL in R. Cross-platform functionality like such makes RStudio way ahead of its competition. A couple of chinks in RStudio armor are very small and can be considered as nagging just for the sake of argument. Other than completely based on programming language, I couldn't find significant drawbacks to using RStudio. It is one of the best free software available in the market at present.
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.
The support is incredibly professional and helpful, and they often go out of their way to help me when something doesn't work.
The one-click publishing from RStudio Connect is absolutely amazing, and I really like the way that it deploys your exact package versions, because otherwise, you can get in a terrible mess.
Python doesn't feel quite as native as R at the moment but I have definitely deployed stuff in R and Python that works beautifully which is really nice indeed.
Python integration is newer and still can be rough, especially with when using virtual environments.
RStudio Connect pricing feels very department focused, not quite an enterprise perspective.
Some of the RStudio packages don't follow conventional development guidelines (API breaking changes with minor version numbers) which can make supporting larger projects over longer timeframes difficult.
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.
There is no viable alternative right now. The toolset is good and the functionality is increasing with every release. It is backed by regular releases and ongoing development by the RStudio team. There is good engagement with RStudio directly when support is required. Also there's a strong and growing community of developers who provide additional support and sample code.
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.
I think it's a quick and easy to use tool. The IDE is very intuitive and easy to adapt to. You do not need to learn a lot of things to use this tool. Any programmer and a person with knowledge or R can quick use this tool without issues.
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.
RStudio is very available and cheap to use. It needs to be updated every once in a while, but the updates tend to be quick and they do not hinder my ability to make progress. I have not experienced any RStudio outages, and I have used the application quite a bit for a variety of statistical analyses
Alteryx is an extremely reliable platform. If there is an error in my workflow, I feel pretty strongly it was probably my fault. The platform also handles large amounts of data very quickly and can join/match, sort, filter, calculate on that data quickly as well. One of my favorite things to build into a workflow are the messages based on data/metadata and error messages based on errors I have come across before.
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
Since R is trendy among statisticians, you can find lots of help from the data science/ stats communities. If you need help with anything related to RStudio or R, google it or search on StackOverflow, you might easily find the solution that you are looking for.
1st level of trainings which I've attended in Paris was easy and I was already knowing %90, that learning could have been an e-learning instead of in-person
Very good, detailed online trainings which you can take at your own pace, and strong certifications exists, certifications are extremely detailed and hard...
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.
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.
RStudio was provided as the most customizable. It was also strictly the most feature-rich as far as enabling our organization to script, run, and make use of R open-source packages in our data analysis workstreams. It also provided some support for python, which was useful when we had R heavy code with some python threaded in. Overall we picked Rstudio for the features it provided for our data analysis needs and the ability to interface with our existing resources.
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.
RStudio is very scalable as a product. The issue I have is that it doesn't necessarily fit in nicely with the mainly Microsoft environment that everybody else is using. Having RStudio for us means dedicated servers and recruiting staff who know how to manage the environment. This isn't a fault of the product at all, it's just part of the data science landscape that we all have to put up with. Having said that RStudio is absolutely great for running on low spec servers and there are loads of options to handle concurrency, memory use, etc.
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.
Using it for data science in a very big and old company, the most positive impact, from my point of view, has been the ability of spreading data culture across the group. Shortening the path from data to value.
Still it's hard to quantify economic benefits, we are struggling and it's a great point of attention, since splitting out the contribution of the single aspects of a project (and getting the RStudio pie) is complicated.
What is sure is that, in the long run, RStudio is boosting productivity and making the process in which is embedded more efficient (cost reduction).
