Great company and team that are vested in your success
We use DataRobot for traditional ML/AI use cases from R&D and training to deploying and monitoring. Use cases include churn / acquisition …
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What is DataRobot?
The DataRobot AI Platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that…
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Popular Features
- Automated Machine Learning (54)9.393%
- Single platform for multiple model development (51)9.090%
- Automatic Data Format Detection (51)8.484%
- Visualization (51)8.080%
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What is DataRobot?
The DataRobot AI Platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that gives users AI to drive business…
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What is DataRobot?
The DataRobot AI Platform is presented as a solution that accelerates and democratizes data science by automating the end-to-end journey from data to value and allows users to deploy AI applications at scale. DataRobot provides a centrally governed platform that gives users AI to drive business outcomes, that is available on the user's cloud platform-of-choice, on-premise, or as a fully-managed service.
The solutions include tools providing data preparation enabling users to explore and shape data in preparation for machine learning, automate machine learning, deploy, monitor, manage, and govern all AI models (i.e. MLOps), and the ability to generate time series models that predict the future values of a data series based on its history and trend.
The solutions include tools providing data preparation enabling users to explore and shape data in preparation for machine learning, automate machine learning, deploy, monitor, manage, and govern all AI models (i.e. MLOps), and the ability to generate time series models that predict the future values of a data series based on its history and trend.
DataRobot AI Platform extends the user's data science expertise with automation and aims to give unlimited flexibility for both data science experts and non-technical users to succeed with AI.
DataRobot Features
Platform Connectivity Features
- Supported: Connect to Multiple Data Sources
- Supported: Extend Existing Data Sources
- Supported: Automatic Data Format Detection
- Supported: MDM Integration
Data Exploration Features
- Supported: Visualization
- Supported: Interactive Data Analysis
Data Preparation Features
- Supported: Interactive Data Cleaning and Enrichment
- Supported: Data Transformations
- Supported: Data Encryption
- Supported: Built-in Processors
Platform Data Modeling Features
- Supported: Multiple Model Development Languages and Tools
- Supported: Automated Machine Learning
- Supported: Single platform for multiple model development
- Supported: Self-Service Model Delivery
Model Deployment Features
- Supported: Flexible Model Publishing Options
- Supported: Security, Governance, and Cost Controls
Additional Features
- Supported: Automated Time Series
- Supported: Cloud-Hosted Notebooks
- Supported: Data Preparation
- Supported: Feature discovery
- Supported: MLOps
- Supported: No Code AI App Builder
- Supported: AI Apps
- Supported: Decision Flows
- Supported: Bias Testing and Monitoring
- Supported: Compliance Documentation and Prediction Explanations
- Supported: Anomaly Detection
- Supported: Data Prep Automation
- Supported: Bringing together any type of data from any source
- Supported: Demand Forecasting
DataRobot Screenshots
DataRobot Videos
DataRobot Integrations
- Snowflake
- Amazon Web Services
- Microsoft Azure
- Highspot
- Automation Anywhere
- FactSet
- Palantir Foundry
- Google Cloud Platform
- Qlik
- Tableau
- UI Path
- KX
- ServiceNow
- Salesforce
DataRobot Competitors
DataRobot Technical Details
| Deployment Types | On-premise, Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Windows, Linux, Mac |
| Mobile Application | No |
| Supported Countries | Global |
| Supported Languages | English, Spanish, French, Korean, Japanese, Portuguese |
DataRobot Downloadables
Frequently Asked Questions
DataRobot starts at $0.
Reviewers rate Automated Machine Learning highest, with a score of 9.3.
The most common users of DataRobot are from Mid-sized Companies (51-1,000 employees).
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(84)Attribute Ratings
Reviews
(1-3 of 3)Companies can't remove reviews or game the system. Here's why
August 09, 2022
A Robust System for Forecasting and Inventory Management.
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.
- 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.
- 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.
75%
7.5
85%
8.5
70%
7.0
80%
8.0
45%
4.5
- Increased Revenue: With DataRobot, I was able to identify items that should have more inventory which gets us more sales for those items instead of being out of stock on them.
- Fewer Inventory Expenses: DataRobot also identifies items where we are overstocked and should not be buying more inventory for them.
- Better Vendor Relationships: DataRobot gives us more accurate forecasting, which allows us to share more accurate information with our vendors for items we would like to see them stock more and allows us to give them more accurate estimates of how many units we plan to purchase from them for the next months/year.
I'm not sure if we use their end-to-end platform for our forecasting. If that's just talking about DataRobot itself, it has benefitted us by giving us more accurate forecasting for our inventory management.
Our organization faces a competitive marketplace and rises and dips in demand, especially with the pandemic and potentially new health-related crises on the horizon. DataRobot allows us to keep our inventory levels healthy and as optimal as possible so our revenue potential is maximized and we are tying up less capital into inventory.
3
Supply Chain and Inventory Management. Accounting, Systems Development
1
An attention to detail and knowing the platform
- Inventory Management
- Purchase Reporting to Vendors
- Projected Revenues
- None yet
- None yet
Yes
It was an internal forecasting system we developed, but DataRobot has proven to be more accurate.
- Product Features
I did not make the decision to use purchase it, but the features they offered was by far the biggest selling point from what I understand.
I would not change anything
March 26, 2022
DataRobot Makes My Life So Much Easier
Acting as a credit broker, I use DataRobot to allow me to rapidly build and deploy machine learning models to predict the likelihood that a loan application will be accepted by a lender; that the consumer will engage with the offer; that the consumer and lender will agree terms and a loan will be funded. Identifying populations with a low probability allows me to reduce costs to lenders in scoring loan applications; and improves the earnings per referral that our partners use to measure our performance.
- Automated machine learning
- Measuring feature impacts and effects
- Producing live probability scores
- Error notification - it can be challenging to identify the cause of errors
- Exporting data from the GUI is not possible
- Complicated commercials which regularly change
62.5%
6.3
35%
3.5
70%
7.0
90%
9.0
80%
8.0
- We have been able to cut costs by not buying leads that we will not be able to sell on
- We have been able to deploy loan eligibility reporting which brought in new business
- We have been able to improve the performance of our credit providers and our partners which has helped to retain business
Using DataRobot to manage the end-to-end AI process has led to significant time savings due to being able to completely automate all interactions with the DataRobot process via Python.
We were already using a trial, so the move from trial to full was instantaneous.
As a trailblazer, DataRobot is a more polished platform
1
Data Science / Analytics
1
SQL, Python, some stats knowledge is useful, as it data science knowledge
- Generating loan eligibility scores
- Filtering out low probability applications
- Maximising Earnings Per Referral
- Insight into credit score feature effects
- Deploying to other territories
- marketing decisions
- Combating customer churn
No
- Product Features
December 25, 2021
DataRobot Provides State-of-the-Art ML Automation
We use DataRobot to address several uses cases across clinical, financial, and operational areas. In the clinical setting, we are looking to predict specific outcomes, like readmissions, in an effort to adjust reduce the readmission rate. The operations team uses outputs from DataRobot to forecast census levels that potentially impact our financials.
- Rapid model building
- Excellent model explanations
- Easy to use API
- State-of-the-art model management and MLOps
- Superb UI
- Scenario building and What-if analysis
- Add prescriptive analytics capability
- Tighter integration with visualization tools
- Classification Predictions
- Time-Series Forecasts
- Model Management
- Prediction API
75%
7.5
85%
8.5
67.5%
6.8
97.5%
9.8
85%
8.5
- Demonstrable decrease in readmission rates (decreases are good)
- Better census forecasting and financial planning
- Improved patient care where it is need, improving patient ratings
We selected DataRobot for its "Automated" Machine Learning. Automation allows us to easily and quickly create machine learning models. The deployment process is simple, which was another key decision factor in choosing DataRobot over other platforms. We were pleasantly surprised by the Model Management functionality of DataRobot. Although Model Management (MM) was not a factor in our initial purchase, it was a factor in our renewal of the platform. I can't see us moving away from DataRobot unless the competitor had solid model management.
No
- Price
- Product Usability
Usability was our most important factor. Our team is comprised of data analysts, not data scientists. So we needed a platform that analysts, with a basic ML understanding, could use. It was clear in the POC phase that our team could spin up models quickly, deploy them, and score results.
Our evaluation of DataRobot included a 60 day POC. The DataRobot team met with us weekly to make sure we were on the right track. We chose a highly visible and relevant use case, so that helped gain traction with the executive team. I would change anything about our approach, it was nearly perfect.