An ideal end-to-end AutoML solution and force multiplier for skeleton crews!
October 07, 2023

An ideal end-to-end AutoML solution and force multiplier for skeleton crews!

Anonymous | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with DataRobot

As Australia's largest radiology business, we use it as part of our sales and outreach program to identify referring doctors who we need to prioritise contact with for a variety of goals including retention and growth. The models trained and deployed on DataRobot assist with this prioritisation process. The output of the model is effectively a risk or opportunity score on how likely a doctor will either increase or decrease in referrals to our clinics if we do not check in on them.

Pros

  • autopilot for testing and ranking the suitability of multiple models
  • easy to upload observations and download the predictions with explanations
  • scalable with multiple workers to speed up the process where urgent

Cons

  • more lenience with uploaded observations when the feature tables don't fully match the feature set that the deployed model trained on. Instead of simply erroring out, provide prompts for in-place fixes.
  • null correlation analysis (how often two columns are missing values at the same time) would be very useful to help identify a different type of data relationship.
  • Helped with loss prevention; measureable value
  • Influenced workloads by our sales team
  • Improved impact per contact hour by sales team.
Comparable to H2O but my company chose DataRobot so that's why I'm using it. Pricing is reasonable and the feature coverage is probably better from an end-to-end perspective. DataRobot has less flexibility than Amazon SageMaker but is a lot simpler to use, which again for a small team is beneficial and a force multiplier in the short term until the organisation matures and invests in largest in-house IT teams to support the AI programs.

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?

Yes

Would you buy DataRobot again?

Yes

Most problems I've encountered in my career can be framed as supervised machine learning problems, and adequately solved with a fairly common workflow and popular ML model families such as xgboost and lightgbm. DataRobot is one of the most low barriers to entry but still complete solutions I have encountered. I appreciate the autopilot system and found that it is an excellent starting point for a project and in some instances running it in comprehensive mode is sufficient to arrive a deployment-ready model that can fit into a BAU. Even entry-level data scientists would be able to hit the ground running with DataRobot and produce a lot of value for their organisation. The only aspect that might limit utility is data preparation, especially domain-specific requirements and sensitive data that cannot be uploaded in a raw form to a cloud hosted service outside of Australia due to privacy concerns.

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