Reviews (1-3 of 3)
July 27, 2020
Score 1 out of 10
We attempted to use DataRobot in our finance and analytics organization. We believed it would help with a few specific projects. Specifically we wanted to use DataRobot to help predict shopping conversion behavior for our customer base and to help assign the right designers to the right projects.
Read Shanna Tellerman's full review
I would not recommend this software to a company that does not have a data science team and engineering team fully ready to support the integration and use.
September 14, 2019
Score 10 out of 10
We are using DataRobot to solve Marketing use cases, such as propensity to buy, ideal customer profiles, lead scoring, and behavioral purchasing trends for customer engagement. For Finance, we are using it to forecast revenue more accurately.
- The interface is easy to use and self-service, with intuitive design.
- The product is easy to use for data analysts and business users without having to be a data scientist, but if you are one the product is robust, so data scientists can also get some use.
- All of the screens have explanations of all data points, models, and this makes it easy to provide explanations at the executive level and can easily modify models on the fly.
- Not having any data cleansing or ETL capabilities, as most of the time you need to clean the data or append data before running models.
- There are constraints to how many models can be run, so this is frustrating, but this is how the pricing model works.
- It would be nice to have some me plug and play APIs for Salesforce and other tools instead of having to build your own.
Read Jerry Gage-Anderson's full review
DataRobot is well suited for business analysts, data analysts, and data scientists. The platform explains its models and predictions in common language so that even executives and non-data analytical folks can understand.
We are using DataRobot as a department-wide software system for analytics on predictability on the Information Technology sector of our firm. Mainly we are utilizing the program for best practices in order to assist in company-wide decision making. It has addressed various manpower issues by yielding a level of automation that eases use of machine learning tasks, basically by displaying helpful predictive models.
- 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.
- The importance of realizing that most software programming in the Predictive Analysis genre is not 100% ideal cannot be overstated. It's tough to locate a program that would fulfill every need of every business type and size. Though DataRobot is about as close as it gets, it may not be for every industry.
- Though DataRobot helps to capture six sigma techniques, knowledge, and expertise of the best data scientists in the nation, it may end up causing rifts in intercompany personnel due to fear of job loss on a long term scale.
- Though fairly priced for a firm of our size and capability, it may be out of market reach for smaller companies at this point. It's important for every firm to understand exactly what they need and can afford.
Read this authenticated review
DataRobot is equipped to serve both cloud computing and on-premise work. Its comprehensive cloud module, channeled through Amazon sustains highly flexible machine learning programs. Lower than average costs are provided via cloud networking because there is no need to install hardware and the additional pricing that comes along with that. DataRobot assists in eliminating hassle by offering various methods of deployment in regard to predictive modeling. The program may not be appropriate for smaller startups of 20 or fewer employees, mainly because the exportable prediction code, and native batch scoring may not translate as well to a smaller firm.