Likelihood to Recommend Data Robot is a powerful tool for greatly reducing the time required to build powerful and accurate machine learning models. It then allows you to utilize these items. It is probably most appropriate for organisations looking to get into data science and incorporate Machine learning and AI into their decision making. Having dedicated resources that can be upskilled is perfect, as the expertise and software provided allows for a big jump from willing to able. For the to work effectively, organisations should really consider dedicating at least one resource to the ML and AI projects, and understsand that not every project will yield fruit. A lot of this is innovation and experimentation, so relying on data Robots insights in make or break situations is not recommended. You also need to manage expectations well as the data you have may simply not allow for a powerful model. Finally, the organisation must be open to change, this has to exist in tandem with the above. If the organisation's key stakeholders don't want to change, all the insights in the world won't help. So a willingness and ability to change effectively is required to maximize ROI.
Read full review 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.
Read full review Pros DataRobot helps, with algorithms, to analyze and decipher numerous machine-learning techniques in order to provide models to assist in company-wide decision making. Our DataRobot program puts on an "even playing field" the strength of auto-machine learning and allows us to make decisions in an extremely timely manner. The speed is consistent without being offset by errors or false-negatives. It encompasses many desired techniques that help companies in general, to reconfigure in to artificial intelligence driven firms, with little to no inconvenience. Read full review 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. Read full review Cons The platform itself is very complicated. It probably can't function well without being complicated, but there is a big training curve to get over before you can effectively use it. Even I'm not sure if I'm effectively using it now. The suggested model DataRobot deploys often not the best model for our purposes. We've had to do a lot of testing to make sure what model is the best. For regressive models, DataRobot does give you a MASE score but, for some reason, often doesn't suggest the best MASE score model. The software will give you errors if output files are not entered correctly but will not exactly tell you how to fix them. Perhaps that is complicated, but being able to download a template with your data for an output file in the correct format would be nice. Read full review 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. Read full review Likelihood to Renew DataRobot presents a machine-learning platform designed by data scientists from an array of backgrounds, to construct and develop precise predictive modeling in a fraction of the time previously taken. The tech invloved addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics. DataRobot utilizes parallel processing to evaluate models in R, Python, Spark MLlib, H2O and other open source databases. It searches for possible permutations and algorithms, features, transformation, processes, steps and tuning to yield the best models for the dataset and predictive goal.
Read full review 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.
Read full review Usability 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.
Read full review Reliability and Availability 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
Read full review Support Rating As I am writing this report I am participating with Datarobot Engineers in an complex environment and we have their whole support. We are in Mexico and is not common to have this commitment from companies without expensive contract services. Installing is on premise and the client does not want us to take control and they, the client, is also limited because of internal IT regulations ,,, soo we are just doing magic and everybody is committed.
Read full review 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.
Read full review Implementation Rating We did it at the individual level: anyone willing to code in R can use it. No real deployment involved.
Read full review Alternatives Considered DataRobot provided the perfect balance of features and price points. The other tools we tried were very expensive and provided extra things that we really didn't need. Some of the other tools also required you to host them on a server at your institution or pay for their cloud service in addition to getting the software. This added to the expense without adding any additional functionality.
Read full review 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.
Read full review Scalability 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.
Read full review Return on Investment We have been able to cut costs by not buying leads that we will not be able to sell on We have been able to deploy loan eligibility reporting which brought in new business We have been able to improve the performance of our credit providers and our partners which has helped to retain business Read full review 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). Read full review ScreenShots