DataRobot provided a swift, powerful, and automatic way to implement large data project in parallel
December 30, 2022

DataRobot provided a swift, powerful, and automatic way to implement large data project in parallel

Anonymous | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Overall Satisfaction with DataRobot

The DataRobot has great cloud computing and multitasking power for feeding large quantity of data. There are time series, categorical, and numerical related target variable for analysis. The whole bucket preprocessing sometimes could help you to save a lot of times. However in the real scenario it would still be better to do most of the preprocessing manually to avoid confusion regarding data type. The post parameter tuning could be more intuitive and would be better to make the replication of model result easier.
  • Computing speed
  • Running in batches
  • Shared projects
  • Post parameter tuning
  • Model result replication
  • Better predicting the Loss Ratio
  • Quicker for parameter tuning
The AI platform serves a great repository for all kinds of projects for testing and tuning. The result comparison between different projects are good to follow.
Having a lot of null values for certain households and datarobot could automatically fill it. Having huge feature space that needs high computing power to do the models efficiently.

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?

I wasn't involved with the selection/purchase process

Did implementation of DataRobot go as expected?

I wasn't involved with the implementation phase

Would you buy DataRobot again?

Yes

The large amount of household specific data with huge feature space is great for DataRobot to run. The result visualization is also easy to follow. However it would be better if there are more NN models could be implemented if possible.

DataRobot Feature Ratings

Connect to Multiple Data Sources
8
Extend Existing Data Sources
6
Automatic Data Format Detection
6
MDM Integration
6
Visualization
8
Interactive Data Analysis
8
Interactive Data Cleaning and Enrichment
7
Data Transformations
7
Data Encryption
5
Built-in Processors
7
Multiple Model Development Languages and Tools
9
Automated Machine Learning
9
Single platform for multiple model development
9
Self-Service Model Delivery
9
Flexible Model Publishing Options
6
Security, Governance, and Cost Controls
6