Item: DataRobot
Rating: 10
Author: Verified User

Overall Satisfaction with DataRobot

Use Cases and Deployment Scope

DataRobot builds machine-learning models to predict creditworthiness of bond issuers.

Pros and Cons

Pros

Manages messy data.
Evaluates numerous models with little user effort
Provides reliable repository for data and models.

Cons

DataRobot is NOT the limiting factor in the improvement of my business process. Getting more and cleaner data is the problem, so, in a sense, DataRobot cannot be improved for my purposes.

Return on Investment

DataRobot has a huge positive impact. It has allowed a single analyst to implement automated analysis applied to thousands of bond issuers.

I have not used any comparable products. Compared to using commonly available open source libraries for machine learning, DataRobot automatically manages the partition of data, pre-processing of data, construction of processing pipelines and the evaluation of models on an equal basis. The time savings compared to constructing ones own processes are enormous.

Key Insights

Do you think DataRobot delivers good value for the price?

Yes

Are you happy with DataRobot's feature set?

Yes

Did DataRobot live up to sales and marketing promises?

Yes

Did implementation of DataRobot go as expected?

Yes

Would you buy DataRobot again?

Yes

Other Software Used

Anaconda, Microsoft Excel

Likelihood to Recommend

DataRobot saves the user an enormous amount of time by automatically implementing best practices related to feature management, partitioning data and evaluating models. DataRobot also provides a "learn on the job" experience in that users with limited knowledge and experience can immediately get useful results and then learn later about the technical details of modeling and handling data.

Comments

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DataRobot is an excellent way to jumpstart a machine-learning project