DataRobot serves as our data science platform for building machine learning models and the development environment for running models. We also use the best practice processes and governance that DataRobot provides, and we are interested in leveraging the commercial value that DataRobot enables. A specific example of how I use DataRobot in my work is the speed at which you can get a model to market and the ability to manage models in production, which is excellent. We also use DataRobot to deploy models and deploy AI solutions that are straightforward and do not require heavy processing. We have integrated this software into the toolbox of our data scientists so that they are able to produce production-grade models in a very short time.
My main use case for DataRobot is to perform predictive analysis and automation of machine learning workflows. I use it to quickly build, test, and deploy models without extensive coding. One of the examples is I use DataRobot to predict which students are likely to accept the university offer. It basically helps us and the admission team to focus their efforts more efficiently. It also helps us with data matching and cleaning in large data sets, which reduces manual work. The prediction helps our team and the admission team to prioritize outreach to the students who are most likely to accept the offer. They inform marketing and follow-up strategies as well, making efforts more efficient and quicker. One example is if DataRobot predicts a student has a high likelihood of accepting, the team can send personalized emails or call them to provide guidance and support directly to these students. It basically focuses on these specific students which have been just highlighted by DataRobot. It also reduces time spent on students who are unlikely to enroll, allowing us to use our resources more efficiently only on the people who we think are actually going to come back and enroll with us. I do use DataRobot for many other things as well. For example, other than the target of student enrollment, I use DataRobot for data cleaning. I do the cleaning of deduplication as well. I also use this to detect any anomalies. It basically helps me to automate all the repetitive tasks and saves me some time. One example I can share is I use it to flag duplicate student records across multiple systems, which used to take us hours to do before, and now it's done a lot more quickly by using DataRobot.
Staff Specialist Data Scientist at a tech vendor with 5,001-10,000 employees
MSP
Top 10
Feb 12, 2025
In our day-to-day use, I utilize DataRobot to speed up our development process through its GUI capability. Once I set up our connection with a back-end data set, whatever the project I work on next, it automatically integrates the data and catalogs. I can continue with feature engineering, prediction modeling, and deployment all in one place. I bring in data and train models using GUI and API methods.
Head of Data and Analytics at a manufacturing company with 501-1,000 employees
Reseller
Apr 4, 2022
DataRobot is used to create models and monitor them as an MLOps. Additionally, to work as pre-processing, to create more features based on their data. It's helping build models much better. By using DataRobot you are using data science capabilities. The type of deployment model depends on the company, but a lot prefer the cloud rather than on-premise. However, some specific data needs to be not on-premise. Most companies want to be in the cloud, but not all the data is relevant there.
Data Scientist at a tech services company with 11-50 employees
Real User
Dec 11, 2019
We are a healthcare startup, so we work with both the healthcare insurance providers as well as the hospitals. We are developing a robotic process automation system for both the insurance part and the hospital side of the healthcare industry. In that operating process automation, we plan to imbibe intelligence, with the help of machine learning.
DataRobot captures the knowledge, experience and best practices of the world’s leading data scientists, delivering unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot enables users to build and deploy highly accurate machine learning models in a fraction of the time.
DataRobot serves as our data science platform for building machine learning models and the development environment for running models. We also use the best practice processes and governance that DataRobot provides, and we are interested in leveraging the commercial value that DataRobot enables. A specific example of how I use DataRobot in my work is the speed at which you can get a model to market and the ability to manage models in production, which is excellent. We also use DataRobot to deploy models and deploy AI solutions that are straightforward and do not require heavy processing. We have integrated this software into the toolbox of our data scientists so that they are able to produce production-grade models in a very short time.
My main use case for DataRobot is to perform predictive analysis and automation of machine learning workflows. I use it to quickly build, test, and deploy models without extensive coding. One of the examples is I use DataRobot to predict which students are likely to accept the university offer. It basically helps us and the admission team to focus their efforts more efficiently. It also helps us with data matching and cleaning in large data sets, which reduces manual work. The prediction helps our team and the admission team to prioritize outreach to the students who are most likely to accept the offer. They inform marketing and follow-up strategies as well, making efforts more efficient and quicker. One example is if DataRobot predicts a student has a high likelihood of accepting, the team can send personalized emails or call them to provide guidance and support directly to these students. It basically focuses on these specific students which have been just highlighted by DataRobot. It also reduces time spent on students who are unlikely to enroll, allowing us to use our resources more efficiently only on the people who we think are actually going to come back and enroll with us. I do use DataRobot for many other things as well. For example, other than the target of student enrollment, I use DataRobot for data cleaning. I do the cleaning of deduplication as well. I also use this to detect any anomalies. It basically helps me to automate all the repetitive tasks and saves me some time. One example I can share is I use it to flag duplicate student records across multiple systems, which used to take us hours to do before, and now it's done a lot more quickly by using DataRobot.
In our day-to-day use, I utilize DataRobot to speed up our development process through its GUI capability. Once I set up our connection with a back-end data set, whatever the project I work on next, it automatically integrates the data and catalogs. I can continue with feature engineering, prediction modeling, and deployment all in one place. I bring in data and train models using GUI and API methods.
We work on AI and ML use cases related to technology and IT.
I did a proof of concept (POC) at DISH Wireless (company name) before they were about to sign a contract. Currently, I'm working on another POC.
DataRobot is used to create models and monitor them as an MLOps. Additionally, to work as pre-processing, to create more features based on their data. It's helping build models much better. By using DataRobot you are using data science capabilities. The type of deployment model depends on the company, but a lot prefer the cloud rather than on-premise. However, some specific data needs to be not on-premise. Most companies want to be in the cloud, but not all the data is relevant there.
We are a healthcare startup, so we work with both the healthcare insurance providers as well as the hospitals. We are developing a robotic process automation system for both the insurance part and the hospital side of the healthcare industry. In that operating process automation, we plan to imbibe intelligence, with the help of machine learning.