DataRobot

DataRobot

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Top Rated
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Score 8.7 out of 100
Top Rated
DataRobot

Overview

What is DataRobot?

The DataRobot AI Cloud 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...
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Recent Reviews

DataRobot delivers

8 out of 10
August 17, 2022
DataRobot helps us make sense of a large amount of information. Trying to predict what's going to happen is always difficult, but with …
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How DataRobot Differs From Its Competitors

Comprehensive Platform

Having a single platform to fit, evaluate and run all of our models for credit analysis was crucial to the success of the project. Constraints of time and personnel would have been prohibitive were it not for the automation and comprehensiveness of the DataRobot platform. The ongoing routine of …
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AI Solutions

A modeling platform like DataRobot has appropriately put the focus of our efforts on acquiring data, which it, ultimately, the lifeblood of the automated credit analysis process. DataRobot has offloaded an enormous burden of researching best practices, coding and evaluation of models. The time and …
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Comprehensive Platform

Personally, things go faster. I'm able to get at answers that I couldn't reach before, and at a fraction of the time. While it does take a bit to train up models with the data sources we're able to import, it's much better than not being able to do it at all or doing the modeling manually. It also …
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AI Solutions

We're always trying to find the next best thing for our clients. The ability to figure out when change is coming and how to adapt when it happens. Being able to see all this faster let's us get our work ahead of the 8-ball and really make sure we stand out.
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Comprehensive Platform

The first and very important thing was the user-friendly interface that allow us to accelerate the adoption of a new platform within our organization. Once the adoption was engaged, we started to support our business areas in a more understandable and faster way in order to contribute in the …
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AI Solutions

Stablish a Data-Driven Culture in the organization was our main objective at the beginning of our Journey with DataRobot. In the past it was very difficult because the datamodelling capabilities were too limited.
We started with small projects for then, take more complex use cases in other business …
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Comprehensive Platform

Reduced the amount of time spent in creating models and allows me to better learn about the relationship the predictors have with the response variable with the number of reports generated per model.
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AI Solutions

Sales are facing a downturn as the popularity of the product portfolio is a highlight variable. DataRobots AI tools have helped me produce many more predictive models aimed at increasing revenue or reducing costs in a much shorter amount of time.
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Comprehensive Platform

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.
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AI Solutions

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 …
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Comprehensive Platform

We have benefited by having increased four-year graduation and one-year retention rates for our students. Through the use of the tool, we have also been able to gain a greater understanding of the factors that pose a risk to student success within our institution and the relative effects of each. …
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AI Solutions

The biggest challenge that our institution faced was being able to manage and increase the success of our large student population. With almost 60 000 students and limited institutional resources, it was essential that we were able to proactively identify which students were at risk and which ones …
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Comprehensive Platform

We only use the core product that DataRobot originally offered. Since their inception, they have acquired and integrated various companies for various purposes: ML Ops, Neutonian for time series model, Paxata for data hygiene, and smaller ones. We have tried several of these out but didn't find …
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AI Solutions

Building models quickly, deploying them quickly and having peace of mind that they will continue running without major issues (outside of data drift, which we monitor). Marketing has transformed into an exercise in building the best predictive models to target a [potential] customer base, and …
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Comprehensive Platform

  • The platform alleviates the cumbersome and lengthy former process associated with model design and formulation.
  • It streamlines multiple algorithms that can be tested and used to validate results.
  • Simple interface that allows modeling, simulation, and sensitivity analysis both from an operational …
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AI Solutions

  • DataRobot has helped us navigate a harsh and hostile environment, given high uncertainty and ambiguity regarding loan decision-making.
  • DataRobot's platform has saved loads of time and effort that would otherwise have been devoted to formulation, programming, and algorithm definition.
  • DataRobot has …
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Comprehensive Platform

I love the idea yet I find that the implementation within AWS doesn't work well with our current internal solution being in a different could.
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Time to Value

Thanks to the very intuitive design and a great knowledge base with plenty of tutorials together with personal support from the DataRobot team, one is good to go within a week or two (assuming a good background in AI and ML is already there). The existing Python module lets more advanced users do …
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Comprehensive Platform

It is easier to have all of the databases together in the same app. You have it all in the same place and later, you can make tests easier because it is all there. There is no maximum amount of space, so it is a good place to have a repository with the information needed.
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Time to Value

It is difficult to start, but later, it is a good tool. You need to do 1 course every 3 days, and also have someone from DataRobot or an external consultancy explain to you and help you learn how to use the tool daily. DataRobot helps you a lot because they want your success.
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Time to Value

If you start on your own maybe it will take a little bit more time but if you go from the DataRobot academy it is immediate. On top of the customer support we receive from DataRobot guys, all your questions are answered on the spot which makes the learning process much faster
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Comprehensive Platform

As a business user, I would definitely struggle to find time to do a full pipeline of ETL + Modelling + MLOps. DataRobot got it all covered for me. I still prefer to do my own ETL, but the modeling and MLOps, that's all on DataRobot.
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Time to Value

From the very start! I built a very interesting model for demand destruction just when Covid19 lockdowns started and had it running in less than a week.
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Comprehensive Platform

Some projects were done exclusively through the platform, but there were instances where it was beneficial to use outside resources. For example for working on data (visualization, joining data) and also for building simpler prototypes and first versions of statistical models instead of artificial …
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Time to Value

We were hindered especially by providing all necessary data in the necessary quality. And by other factors. We are now 6 months into the use of DataRobot and don't have a running ai in production. We started the first few weeks with planning and ideation, then weeks with data exploration and non …
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Comprehensive Platform

A standard approach for any type of data science problem, allowing us in the team to easily understand what anybody is doing, easily changing the person in charge of the project, or reviewing each other's work. Also, less risk when someone from the team leaves the company since their projects can …
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Time to Value

We started using the platform right away, in the week following the opening of the licenses for the team. The first model that we successfully developed was achieved in the first 2 months, and the model was deployed in the third month. In the following two months, that model was officially in …
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Time to Value

It took some months before we had everything up and running. there was quite some struggle with the security part of the integration - can have been fixed now. the results were the from the beginning, because of the fantastic pre-sales data science team.
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Comprehensive Platform

It is easy to integrate with UiPath RPA and with other downstream systems, making it easy to glean data insights and take quick action before problems occur. Using the DataRobot AI Cloud platform has been a boon for our company as a lot of time has been saved and manual intervention has been saved.
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Time to Value

It was really easy to set up and implement and they also had lots of support videos and training guides. We found that we could get our citizen data scientists to implement the AML and this proved a good success as it kept them enthused and we could see the benefits of the product with visible …
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Comprehensive Platform

The short answer is YES. We have only one AI platform for all business needs which is DataRobot, of course. We really do not need any other AI tool at this time. The end users are managers and executives at this time. We want to democratize AI with DR App when available.
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Time to Value

Within 3 months we had two use cases up and running. We have popularized AI and AML - thanks to DataRobot - across all our schools. The Principals love predictive analytics.
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Time to Value

Very quickly since we opted for cloud-based model. Few knowledge sessions were arranged by the sales team for the data analytics team
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Popular Features

View all 16 features
  • Automated Machine Learning (41)
    9.3
    93%
  • Automatic Data Format Detection (40)
    8.2
    82%
  • Visualization (41)
    7.9
    79%
  • Interactive Data Analysis (40)
    7.8
    78%

Reviewer Pros & Cons

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Video Reviews

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Pricing

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What is DataRobot?

The DataRobot AI Cloud 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…

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting / Integration Services

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Features Scorecard

Platform Connectivity

7.7
77%

Data Exploration

7.9
79%

Data Preparation

7.8
78%

Platform Data Modeling

8.7
87%

Model Deployment

8.4
84%
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Product Details

What is DataRobot?

The DataRobot AI Cloud 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.

DataRobot AI Cloud 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

Screenshot of Decision FlowsScreenshot of No Code App BuilderScreenshot of AI AppsScreenshot of Automated Time SeriesScreenshot of MLOpsScreenshot of Model InsightsScreenshot of Visual AIScreenshot of Prediction ExplanationsScreenshot of Bias and FairnessScreenshot of Cloud-Hosted NotebooksScreenshot of Data PreparationScreenshot of Location AI

DataRobot Videos

DataRobot Downloadables

DataRobot Integrations

DataRobot Competitors

DataRobot Technical Details

Deployment TypesOn-premise, Software as a Service (SaaS), Cloud, or Web-Based
Operating SystemsWindows, Linux, Mac
Mobile ApplicationNo
Supported CountriesGlobal
Supported LanguagesEnglish, Spanish, French, Korean, Japanese, Portuguese

Frequently Asked Questions

DataRobot starts at $0.

Dataiku DSS, H2O, and Google Cloud AI are common alternatives for DataRobot.

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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Comparisons

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Reviews and Ratings

 (66)

Ratings

Reviews

(1-25 of 45)
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Score 10 out of 10
Vetted Review
Verified User
DataRobot builds machine-learning models to predict creditworthiness of bond issuers.
  • Manages messy data.
  • Evaluates numerous models with little user effort
  • Provides reliable repository for data and models.
  • 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.
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.
August 17, 2022

DataRobot delivers

Score 8 out of 10
Vetted Review
Verified User
DataRobot helps us make sense of a large amount of information. Trying to predict what's going to happen is always difficult, but with DataRobot we're able to use the power of robots to do the heavy lifting for us. Let's face it — even if we could do all the complex math on our own, the time it would take would be completely prohibitive. DataRobot takes all that on, letting us get to the decision making instead of setting up models.
  • Time Series
  • Modeling
  • Awesome robot predictions
  • Flexibility of certain models
  • Time series included in general base package
  • Certain data source integration
Time series data. Honestly, there's a lot of information that gets collected over time. Using DR, it becomes easier to track what's going on and get to the point where we're predicting what's going to happen. While DR is great at the big picture stuff, a lot of times (for quick/easy answers), it's better to just do the quick math yourself.
Score 8 out of 10
Vetted Review
Verified User
DataRobot is part of our DataScience LifeCycle supporting our team in every stage of the AML process. For each business area in my company, data robot contribute reducing the time for development and also reducing the learning curve when we hire a new member in our team. In terms of scope, i have used DataRobot only for batch predictions and it works very well.
  • Feature Engineering
  • Model Training
  • Metric Validation
  • Detect Bias
  • Direct Connection to Oracle Database
  • Normalize Data
  • Customer Success
DataRobot is a Powerful tool for teams that are beginning in datascience world where learning curve and speed are critical in order to generate value within any organization.

For those teams who have previous experience in datascience, DataRobot always is a good option but you have to be careful of your volumetrics needs such as number of deployments, number of users, etc.
Score 8 out of 10
Vetted Review
Verified User
Predict churn. Identify ideal customers and targeted customers for promotions.
  • Minimizes coding extensively (for the user).
  • Allows high levels of customization.
  • Deployments are well organized.
  • Model training could be faster.
  • Too many limitations, such as making changes to deployments (such as threshold).
Great for straightforward predictive analytic work, such as the quintessential business cases (e.g. churn prediction). Not so good for unsupervised stuff, such as clustering, and it is pretty hard to use to predict recommendations.
Score 8 out of 10
Vetted Review
Verified User
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.
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.
Score 10 out of 10
Vetted Review
Verified User
We use the tool for student success. We make various predictive models for predicting the graduation and retention of our students. We use the predictions to identify at-risk students and refer them to advisors or success coaches for help. For example, if students have less than a 60% probability of graduating within four years based on the predictive model, they will get referred to an advisor for further help. During our use of the tool, we have almost doubled our 4-year graduation rate.
  • Process large amounts of data quickly.
  • Provides very accurate predictions.
  • It provides an easy way to compare the predictive value of each of the features of the model.
  • Has a good text analysis tool.
  • Further improvements to their text analysis tool, to be more like the Qualtrics text analysis tool, would be a great addition. Qualtrics has templates built into their text analysis tool for customer service, quality control, etc, and will automatically slot your text responses into categories associated with certain sub areas of those larger categories.
DataRobot is a very robust and easy-to-use tool. It can be used for practically anything. It works best in cases where you have powerful predictors that are not highly correlated with each other, and you are looking to predict a single outcome variable. If you are trying to predict multiple variables at the same time, you will have to create separate models for each one. While it does provide information about the effectiveness of each predictor, it will not give you a detailed analysis of the interactions between your variables. However, it will let you know if some variables are redundant so they can be removed.
Score 9 out of 10
Vetted Review
Verified User
We build predictive models with the core supervised learning product. These include attribution models, churn/retention models, segmentation models, and others. Basically, anything that can be accomplished by taking a supervised, labeled set of training data and turning it into a predictive model, we use DataRobot. We have also dabbled with unsupervised learning and time series modeling but have not purchased those packages.
  • Iterative model development
  • Fast training of a very large number of models
  • Easy deployment to their cloud solution, or export as an approximate model
  • Visualization and explanation of important model components
  • We should be able to download data sets from our own projects--after all, we uploaded them originally (and they were not stored locally; they were created specifically for a DataRobot project).
  • The sales team is very aggressive at pushing features that we would never use, such as data hygiene (clunky integration of Paxata), ML Ops (just don't need it), and AI services (we're a mature company; we don't need help coming up with use cases).
  • Pricing changes every year--not just the amount but what you actually get, so we need to nitpick the contract each year because DataRobot has inevitably eliminated something we need.
It's appropriate for speeding up the work of your experienced data scientists. If they spend more than 15% of their time building and tweaking models, DataRobot will cut that down significantly. Caveat emptor: while the DataRobot marketing materials promise to turn any analyst into a data scientist, this is far from the truth. If your potential users do not already understand how machine learning models work, and have not built some models on their own, then they will make mistakes that DataRobot will not correct because it assumes you know what you're doing. Interpreting the results and iterating on models is easy for a trained data scientist but would be baffling for a typical financial analyst.
Javier Mendez | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
I use DataRobot to streamline, automate and deploy credit scoring and risk assessment evaluation models for a multinational Fintech with operations across different LATAM markets.
  • Powerful to quickly connect and process data
  • Excellent algorithm generation and model building capabilities
  • Superior performance to deploy live models with API connectivity
  • Enhanced capabilities to connect to SQL servers is desired.
  • Functionalities oriented to suggest feature improvements and amendments when models decay over time.
  • Formatting is an issue. Standardization and user-friendliness are required whenever working with local spreadsheets, CSVs, and other data repositories.
DataRobot is tailored to efficiently automate algorithm generation and model testing based on industry-specific best practices. It is user-friendly, well-designed, and capable enough to develop world-class classification predictive models with a reliable monitoring interface.

It is well suited to carry out forecasts and feed from massive amounts of data to simplify decision-making in a seamless, comprehensive, and applicable manner.
Score 8 out of 10
Vetted Review
Verified User
Exploratory data analysis including time series as well as forecasting and building prediction models.
  • Feature engineering
  • Time series
  • Forecasting
  • An on premise solution instead of cloud for use with very sensitive data
  • Integration with MS Azure
  • Classification
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.
Score 8 out of 10
Vetted Review
Verified User
DataRobot is a very useful tool to quickly look for interactions and relations between different features. It serves as a comfortable way to engineer features and rapidly interpret behaviors in between specific attributes.
  • Feature engineering
  • Performance and velocity estimation
  • Overall management of several models at once
  • Integration with external data sources could be easier
From a credit risk perspective, I think DataRobot is very useful to work on scenario assessments. For example, to identify the worst possible scenario in a default assessment.
Our company had a dedicate scientist ready to answer any question, no matter the degree of complexity and the overall mathematical proficiency.
March 29, 2022

A Good AI Tool

Score 9 out of 10
Vetted Review
Verified User
We use DataRobot as scoring to underwrite new policies. It is an additional help to know who will be a good insurer and who will not. You can use DataRobot to predict something that you need. Our business problem is that it is sometimes difficult to know who is going to have a claim and who doesn't.
  • Modeling
  • Easier than others
  • Well explained
  • Courses in Spanish
  • Cheaper
  • Not always intuitive
It is well-suited when you can finally be able to work "easily" when you know how it works. It is not suited when you start to use the tool you need to contract a consultancy, but you have to know how to use it. Also, they have courses you can use, but you have to dedicate the time to study and learn.
I have been using DataRobot since 2020, and they have 4 kinds of people that can help you, and they, for sure, help you. Support helps you with utilizing the tools offered. The key account manager can assist with creating contracts. The money-value data scientists help employees use the tool. Engineers are the deployment experts connecting DataRobot with your company.
Score 9 out of 10
Vetted Review
Verified User
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.
  • Customer support
  • Customer scaling up
  • Give visibility on what other customers are doing in other industries
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
Score 10 out of 10
Vetted Review
Verified User
DataRobot is our data science platform for building ML models and a Dev Ops environment for running models. But we also use the best practice processes and governance that DataRobot gives us. We are interested in providing the commercial value that DataRobot enables.
  • Data Science ops
  • Support
  • Auto ML
  • yet to find a good example
speed in which you can get model to market ability to mange manage in production
Score 9 out of 10
Vetted Review
Verified User
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
DataRobot is great when you have a structured flat dataset and want to predict either regression or categorization. It is not as well matured in dealing with nonstructured data, images, audio recordings, etc. It is great if you can define your features outside of the software, but it is not possible to make changes to the data once you have uploaded, including performing calculations on the data (e.g. adding two features together).
Score 10 out of 10
Vetted Review
Verified User
We use DataRobot to model and deploy AI solutions that are straightforward and do not require heavy pre-processing. We integrated this software into the toolbox of all our data scientists so that they are able to produce production-grade models in a very short time.
  • Automated modelling
  • Model deployment
  • Deployment monitoring
  • Time Series modelling
  • Integration between cloud-based solution and on-premise data
  • More support for NLP
- When business leaders ask for the fastest possible solution, it is the go-to platform. - When you are not experienced with a specific task and you want to test an array of possible models. - When you are not a fully devoted Data Scientist, and therefore cannot spend too much time on fine-tuning model hyperparameters.
Score 9 out of 10
Vetted Review
Verified User
We are mainly using it as a tool to develop ai knowledge and try to take our first steps. For example product recommendations, delivery time prediction, and sales predictions. We are still extremely new and are not currently running a system in live production. But we are seeing the value and are making progress.
  • User Interface
  • Explainability
  • Speed
  • Suitable for extremely unexperienced users
  • Pricing Model
  • Information on in production solutions at similar customers
If there is some experience with data and especially if there are enough resources and time available for users to invest in the projects. It is unsuitable as another side-project that can only have minimal resources. Ideally, there are already some ideas for concrete ai cases that could use the company.
Amar Kumar | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
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.
  • 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.
  • 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
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.
K Aswini Kumar | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
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
  • Hyper parameter tuningoptimization
  • EDA
  • Feature generation
  • Improving model accuracy metrics
  • Improve on Automation
  • Price points can be improved
We used for some of our business problems to get the most appropriate features, producing the solutions and ML scenarios
Ignacio Vilaplana | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Reseller
We use DataRobot to prototype new models that might solve business problems with the data that we have in our data warehouse. The models that have a positive return and fit in our business process are then evaluated and documented, and presented to a commission that approves them. Once they are approved, we also use DataRobot to deploy those models in production and monitor and govern the model in production, measuring the value that it is generating through time.
  • Quickly solving data science problems
  • Monitoring models in production
  • Compare different approaches in solving a problem with AI
  • Integrating the capability to modify with python the whole pipeline
It is especially best suited for companies with many AI use cases due to its rapid prototyping. It is also beneficial when the data science team is not big since it can multiply the productivity of the team, allowing each data scientist to work on more than one project at the same time, leveraging the platform speed. Also good when the data scientists are not experts and can benefit from the guardrails that the platform offers.
Score 1 out of 10
Vetted Review
Verified User
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.
  • Fantastic data scientists
  • solving the problemet
  • not so easy to use when you want a model in production
  • timeseries data analyse
Score 10 out of 10
Vetted Review
Verified User
DataRobot supports prioritized AI/ML use cases, which range from predictive models around financial performance to employee-focused use cases.
  • Platform simple and intuitive.
  • Wonderful support.
  • Product roadmap well managed.
  • Socializing and promoting how their customers are using the platform and deriving value or making an impact.
DataRobot is well suited when the business has really defined its use case well and you have internal SMNE's/resources to support the use cases. In addition, you need people with some data science and/or analytics knowledge. It is less suitable when the above scenarios don't exist.
February 12, 2022

DataRobot is fabulous

Score 8 out of 10
Vetted Review
Verified User
We use DataRobot to predict and classify tickets in our helpdesk system. This has helped to save considerable time in having to manually classify tickets. We have also used the DataRobot/Uipath connector to allocate the automatically classified tickets into the agents' queues without having them manually pick up the tickets for resolution.
  • Use of keys words
  • Accurate prediction of ticket classes
  • Integrates well with UiPath RPA
  • The user interface can be improved
  • Add multi factor authentication to improve security
  • Change the pricing structure to make it more cost effective
Predicting customer churn of our top 30% of our referring doctors and the effects of them doing so Predicting IT service tickets using keyword analysis, so as to save time from having to manually select different categories and sub-categories, eliminating delays for tickets to be picked up by service desk agents.
Score 9 out of 10
Vetted Review
Verified User
We use DataRobot for predictive analytics. We predict student outcomes (to maximize), student exits (to minimize), and such key business priorities based on their previous performance, socio-economic attributes, behavior, wellbeing, school attributes, community attributes, etc. Over 50 input variables in one regression model. Similarly, over 20 variables in another logistic regression model. Use cases are emerging in technology and facilities areas too.
  • Validated algorithms with a wide, composite range
  • Transparent analysis
  • Excellent documentation
  • User friendly, interactive visualisations
  • Connection to Tableau
  • Dark background interface is harder to read
  • Better explainability of features - feature importance vs feature impact etc.
  • Need for an App for what- if analysis
Having DataRobot is like having 100 Data Scientists quietly humming away behind my screen. And, the great thing is these 100 Data Scientists seldom argue and actually agree !! "They" are very efficient too:) Automated Machine Learning is here to stay - it's like outsourcing analytical knowledge and insourcing business knowledge - the best of both worlds for a humble school system with over 43000 students.
Score 9 out of 10
Vetted Review
Verified User
An amazing data analytics platform. Cloud-based solution. User-friendly dashboard. A lot of customization can be done based on business requirements. Gives good output from the raw data. Lots of data fields are available. Nice chart functionality. Different roles are available. We can use it on Prem deployment also. Support multiple data formats. The use case was to increase the visibility of the customer current services which they are using.
  • Easy of access
  • Customized dashboard
  • Ease of integration
  • Support multiple data formats
  • Various templates and reports available
  • Data center in India
  • Detailed Audit trail
  • Integration with inhouse applications
It is good for bfsi industry to use this platform to find details regarding customer needs and their onboarding journeys. Also useful to find out the problem areas from where the organization is not getting the required revenues that could be cross-sold, digital sales, partner sales .etc. This platform may not be useful for tech-related statistics
manish karan | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
DataRobot is super incredible with data engineering. It has a lovely UI. It's simple to deploy and use. Great with real-time reporting by intelligence.
  • It's a magnificent software with business intelligence.
  • It's excellent with instant access of data.
  • Efficient for it's ease of deployment.
  • Intuitive UI.
  • It requires programming skills to use.
  • It's magnificent with being able to collect and manipulate database.
  • Excellent for tracking data with maximum protection.
  • It's great for business intelligence.
It's very superb for business intelligence, and making business decisions. It has intuitive UI, and it's excellent with data consistency.
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