Senior Data Reporting Analyst at a educational organization with 1,001-5,000 employees
Real User
Top 5
Oct 30, 2025
For those looking into DataRobot, I recommend starting with a small project to grasp the workflow before scaling. Utilizing the automations offered and dedicating some time for training is key, along with collaborating and sharing models and dashboards within the team to maximize the platform's value. DataRobot is a powerful, user-friendly platform that saves time and provides accuracy, although improvements are needed in handling larger data sets and flexibility. You can use my real name for the public review. I have provided this review with a rating of 7.
Staff Specialist Data Scientist at a tech vendor with 5,001-10,000 employees
MSP
Top 10
Feb 12, 2025
I would recommend DataRobot because if there is something not included in the UI, I have the freedom to use its Python API, which extends the capability for different use cases. Additionally, I would rate DataRobot eight out of ten for my overall experience.
Data Scientist at a tech services company with 10,001+ employees
Real User
Top 10
Jul 10, 2024
Based on your similar requirements, V10.0 has very cool features related to AI Generation. I would suggest the team, too. This is very good for data scientists or people who don't want to code. Even the documentation is well-maintained in terms of its capabilities. It's easy to navigate. The support documents are good. Even someone with basic IT knowledge can easily navigate. If you're an IT engineer, you can efficiently perform operations using it. We have deployed eight to nine use cases on DataRobot and have seen a tremendous response in accuracy and performance. We are pleased because we conducted a comparison. We took a model we built using a sample Python on a local machine and applied the same data and process using DataRobot Autopilot. The results were pretty amazing, with promising accuracy and recall. The accessibility is so easy. Even a college graduate with essential experience can use it. Suppose I do the same model in Databricks and want to monitor my MLOps pipeline. So, I need to use a third-party framework again, like MLflow, Kubeflow, Airflow, or whatever. I need to build my dashboards and everything, customization dashboards. However, everything is available in DataRobot. I can use it directly. They have a new option called DataRobot apps. So, on the predictions, we can even create customized apps. I can build my dashboard, and I can develop my applications. Overall, I rate the solution an eight out of ten.
The solution itself is definitely nine out of ten. It's a really good solution. If cost is not an issue for most companies, they would love to have DataRobot. That's how most of the clients have been.
Head of Data and Analytics at a manufacturing company with 501-1,000 employees
Reseller
Apr 4, 2022
The business departments will love to work with DataRobot because they use the tool to investigate their data, such as targeting what they want to investigate. They don't need any data scientists near them. They can investigate at eye level and bring into the BI tool, or can bring it to the data scientist. Data scientists can use this tool to bring increase the solution to the maximum. All the others can use it, but not to the maximum. A data scientist can bring it to the maximum level, by fine-tuning it to create a lot of models. However, the BI can be used to build models and investigate their data, and they don't need to understand the mathematics behind it. This is one of the amazing things because on the business side you can use, Business One, BI, and marketing. All these people can work with DataRobot and can create a model or create their vision, and then the BI can build it. I rate DataRobot a ten out of ten.
Data Scientist at a tech services company with 11-50 employees
Real User
Dec 11, 2019
I would recommend this, provided there can be integration of our existing R or Python code. Maybe the structure during the permanent phase of deployment could also be made better. That would help most people. I would rate this solution as eight out of ten.
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.
For those looking into DataRobot, I recommend starting with a small project to grasp the workflow before scaling. Utilizing the automations offered and dedicating some time for training is key, along with collaborating and sharing models and dashboards within the team to maximize the platform's value. DataRobot is a powerful, user-friendly platform that saves time and provides accuracy, although improvements are needed in handling larger data sets and flexibility. You can use my real name for the public review. I have provided this review with a rating of 7.
I would recommend DataRobot because if there is something not included in the UI, I have the freedom to use its Python API, which extends the capability for different use cases. Additionally, I would rate DataRobot eight out of ten for my overall experience.
Based on your similar requirements, V10.0 has very cool features related to AI Generation. I would suggest the team, too. This is very good for data scientists or people who don't want to code. Even the documentation is well-maintained in terms of its capabilities. It's easy to navigate. The support documents are good. Even someone with basic IT knowledge can easily navigate. If you're an IT engineer, you can efficiently perform operations using it. We have deployed eight to nine use cases on DataRobot and have seen a tremendous response in accuracy and performance. We are pleased because we conducted a comparison. We took a model we built using a sample Python on a local machine and applied the same data and process using DataRobot Autopilot. The results were pretty amazing, with promising accuracy and recall. The accessibility is so easy. Even a college graduate with essential experience can use it. Suppose I do the same model in Databricks and want to monitor my MLOps pipeline. So, I need to use a third-party framework again, like MLflow, Kubeflow, Airflow, or whatever. I need to build my dashboards and everything, customization dashboards. However, everything is available in DataRobot. I can use it directly. They have a new option called DataRobot apps. So, on the predictions, we can even create customized apps. I can build my dashboard, and I can develop my applications. Overall, I rate the solution an eight out of ten.
The solution itself is definitely nine out of ten. It's a really good solution. If cost is not an issue for most companies, they would love to have DataRobot. That's how most of the clients have been.
The business departments will love to work with DataRobot because they use the tool to investigate their data, such as targeting what they want to investigate. They don't need any data scientists near them. They can investigate at eye level and bring into the BI tool, or can bring it to the data scientist. Data scientists can use this tool to bring increase the solution to the maximum. All the others can use it, but not to the maximum. A data scientist can bring it to the maximum level, by fine-tuning it to create a lot of models. However, the BI can be used to build models and investigate their data, and they don't need to understand the mathematics behind it. This is one of the amazing things because on the business side you can use, Business One, BI, and marketing. All these people can work with DataRobot and can create a model or create their vision, and then the BI can build it. I rate DataRobot a ten out of ten.
I would recommend this, provided there can be integration of our existing R or Python code. Maybe the structure during the permanent phase of deployment could also be made better. That would help most people. I would rate this solution as eight out of ten.