DataRobot Reviews

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.

DataRobot is equipped with a GUI-based approach that simplifies the process of feature engineering and model training. It provides AutoML capabilities, which allow for comparing thousands of models and selecting the best-suited one based on business requirements. By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month.

We work on AI and ML use cases related to technology and IT.

DataRobot is highly automated, allowing data scientists to build models easily. It excels in MLOps, offering robust solutions. Its platform integrates end-to-end processes, simplifying model building and deployment, which addresses many pain points for data scientists. It has very easy access, and they made everything into a single platform

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.

I used DataRobot extensively at DISH Wireless (my previous company). It's very user-friendly, and the data munching is fast. They have another product that helps with data processing as well. It connects well with Snowflake, which is pretty fast as an engine.

Different models, especially financial ones, run very fast in DataRobot. They have a strong focus on financial applications.

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.

DataRobot can be easy to use.

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.

We especially like the initial part of feature engineering, because feature engineering is included in most engines, but DataRobot has an excellent way of picking up the right features.