Community insights

TrustRadius Insights for DataRobot are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.

Pros

Interface Excellence: Reviewers have consistently lauded the software for its excellent interface, emphasizing its speed, user-friendly development environment, and seamless facilitation of insights sharing with business users. Users find the intuitive design and smooth navigation crucial in enhancing their workflow efficiency and collaboration across teams.

Automodelling Capabilities: Many users have expressed satisfaction with the tool's automodelling capabilities, finding them more than sufficient for their needs. They appreciate the tool's impressive performance and explainability in generating models efficiently. The robust automation features streamline complex modeling tasks, allowing users to focus on interpreting results rather than intricate model building processes.

Support and Deployment Ease: Users highly value the platform's support services and expert technical assistance. They find deployment to be straightforward and stress-free, thanks to the excellent support provided by the platform. The reliable guidance from technical experts ensures a smooth implementation process, enabling users to leverage the platform effectively for their data analytics needs.

Reviews

6 Reviews

Manufacturing

A Robust System for Forecasting and Inventory Management.

Rating: 8 out of 10

Incentivized

August 9, 2022

Use Cases and Deployment Scope

I use DataRobot to forecast our sales each month. DataRobot builds models from the data we give it and then gives us a prediction on what sales are going to be like for the next 90 days. I then use that data to determine how many products we need to purchase for a particular item (in our case, medical apparel). The balance we are trying to find is having enough inventory to sell so we are not out of stock on a particular item while not having too much of our capital tied up into inventory that is not selling. One problem with selling medical apparel is sorting thru all the data and figuring out what data is consequential or what is not (for example, the size of a piece of clothing is consequential, like Large will sell more than X-Small, but fabric type may be less consequential). DataRobot allows me to use machine learning technology to go thru many different data points and to see what is consequential and what is not.

Pros

Provides Charts that show how well their model performs,
Is highly customizable when you're building a model.
Makes a lot of the decisions for you so you don't have to babysit each step.

Cons

The platform itself is very complicated. It probably can't function well without being complicated, but there is a big training curve to get over before you can effectively use it. Even I'm not sure if I'm effectively using it now.
The suggested model DataRobot deploys often not the best model for our purposes. We've had to do a lot of testing to make sure what model is the best. For regressive models, DataRobot does give you a MASE score but, for some reason, often doesn't suggest the best MASE score model.
The software will give you errors if output files are not entered correctly but will not exactly tell you how to fix them. Perhaps that is complicated, but being able to download a template with your data for an output file in the correct format would be nice.

Likelihood to Recommend

If one takes the time to learn the platform, the platform can be very useful for making predictions. It's not perfect, and you do need your real-world insight to determine if their predictions have the potential to be better than an internal system or a rudimentary system or are wildly off, but for our business, just a slight improvement can mean thousands of dollars in both revenue and thousands of dollars of savings from not purchasing items we may have otherwise purchased.

Nathan Walker

Supply Chain Specialist at Piranha Brands (Apparel & Fashion, 51-200 employees)

Vetted Review

1 year of experience

Great place for an automated AI and TS modelling with very nice training programs especially for (junior) analysts

Rating: 8 out of 10

Incentivized

April 5, 2022

Use Cases and Deployment Scope

Exploratory data analysis including time series as well as forecasting and building prediction models.

Pros

Feature engineering
Time series
Forecasting

Cons

An on premise solution instead of cloud for use with very sensitive data
Integration with MS Azure
Classification

Likelihood to Recommend

Great time saver for quick exploratory analysis or testing ideas and possible solutions. Not so good for working with very sensitive data or when additional data anonymization is required.

Verified User

Professional in Research & Development (Cosmetics company, 10,001+ employees)

Vetted Review

2 years of experience

How to become a consumer centric company with the help of DataRobot

Rating: 9 out of 10

Incentivized

March 28, 2022

Use Cases and Deployment Scope

We use DataRobot to build data products such as predictive models that are helping the business to move the needle. We use them mainly to adapt consumer experience now that PMI has become a consumer-facing company (it was not the case before IQOS) This year we are starting a new way of engaging with the business to make them part of the full process.

Pros

Customer support
Customer scaling up

Cons

Give visibility on what other customers are doing in other industries

Likelihood to Recommend

Datarobot is a super powerful and useful tool for all data science teams, especially for those teams which are not specialized but where all team members take care of data products from A to Z ( from data foundation to prescriptive analytics) as the tool is democratizing AI. It is very useful as well to gain time, you do not need to spend hours and hours coding as the platform does it for you already. During the training they are providing, you can experience on your own, that regardless of all the manipulation you can do to the models on your own, you will never beat the machine

Cristina Alvarez

Head of Data & Analytics at PMI (Tobacco, 10,001+ employees)

Vetted Review

3 years of experience

DataRobot Review after 1 year of rigorous use

Rating: 8 out of 10

Incentivized

March 25, 2022

Use Cases and Deployment Scope

DataRobot is used for training several models, evaluating the trained models, deploying them in production, and tracking the result on day to day basis. DataRobot has excellent MLOps support. We are utilizing DataRobot for demand prediction (time-aware models). In another project, we utilized the predictor and optimizer applications for demo purposes.

Pros

It can do feature engineering very well.
It can explain the model and model predictions very well.
The deployment and model management is very easy.
It tries exhaustive list of models before finalizing one.

Cons

It does not provide enough opportunity to modify the pipeline.
Once the control is given to datarobot, there is little that a data scientist can do.
DataRobot can generate explanation for why a model was
Model retraining automation is not very flexible in Datarobot

Likelihood to Recommend

Appropriate When we have a very straightforward data science problem, which needs a scalable solution, then it is a suitable solution. Suitable for time-aware models, DataRobot can created many features. Less Appropriate When the data science problem is challenging and requires lots of fine-tuning, the DataRobot is not a good solution.

Amar Kumar

Senior Data Science Manager in Information Technology at Coats (Textiles, 10,001+ employees)

Vetted Review

1 year of experience

View profile

A good project with exciting future prospects

Rating: 8 out of 10

Incentivized

March 23, 2022

Use Cases and Deployment Scope

DataRobot is really useful for data scientists to start immediately and allows basic asks such as hyperparameter tuning, optimization of parameters, and choosing the right model easily. In the current organization, we use to production the solution and really helped reduce the execution timelines around the projects

Pros

Hyper parameter tuningoptimization
EDA
Feature generation

Cons

Improving model accuracy metrics
Improve on Automation
Price points can be improved

Likelihood to Recommend

We used for some of our business problems to get the most appropriate features, producing the solutions and ML scenarios

K Aswini Kumar

Global BI Manager in Information Technology at Coats (Textiles, 10,001+ employees)

Vetted Review

1 year of experience

View profile

Overselling by saledepartment

Rating: 1 out of 10

Incentivized

March 23, 2022

Use Cases and Deployment Scope

We do not use DataRobot anymore. It was oversold by their sales guy. They have fantastic data scientists who solved the use cases we had, but from there we have not really used it. It turned out it was not the platform that solved the issues but the preprocessing step outside of DataRobot using a python package to do some specific calculations. The main drawback is the pricing structure. so that is what we are doing now. We have tried to do internal roadshows to see if other parts of the organization could use it, but no luck yet.

Pros

Fantastic data scientists

Cons

solving the problemet
not so easy to use when you want a model in production
timeseries data analyse

Likelihood to Recommend

Verified User

Engineer in Manufacturing (Pharmaceuticals company, 1001-5000 employees)

Vetted Review

2 years of experience

Loading Reviews List....

A Robust System for Forecasting and Inventory Management.

Rating: 8 out of 10

Incentivized

August 9, 2022

Use Cases and Deployment Scope

Pros

Provides Charts that show how well their model performs,
Is highly customizable when you're building a model.
Makes a lot of the decisions for you so you don't have to babysit each step.

Cons

The platform itself is very complicated. It probably can't function well without being complicated, but there is a big training curve to get over before you can effectively use it. Even I'm not sure if I'm effectively using it now.
The suggested model DataRobot deploys often not the best model for our purposes. We've had to do a lot of testing to make sure what model is the best. For regressive models, DataRobot does give you a MASE score but, for some reason, often doesn't suggest the best MASE score model.
The software will give you errors if output files are not entered correctly but will not exactly tell you how to fix them. Perhaps that is complicated, but being able to download a template with your data for an output file in the correct format would be nice.

Likelihood to Recommend

Nathan Walker

Supply Chain Specialist at Piranha Brands (Apparel & Fashion, 51-200 employees)

Vetted Review

1 year of experience