DataRobot Reviews and Ratings

Use Cases and Deployment Scope

I use it for predictive analysis. It helps develop credit risk models to be used for various business operations s (i.e., Products, Credit, and Collections), such as cross-selling, credit limit selling, and collection strategy formulation. On the other hand, it helps perform credit risk analysis to formulate solutions and effective risk management strategies. Manpower can also be maintained while increasing productivity thanks to data robot's capabilities.

Likelihood to Recommend

DataRobot can be used for risk assessment, such as predicting the likelihood of loan default. It can handle both classification and regression tasks effectively. It relies on historical data for model training. If you have limited historical data or the data quality is poor, it may not be the best choice as it requires a sufficient amount of high-quality data for accurate model building.

Use Cases and Deployment Scope

We use DataRobot for traditional ML/AI use cases from R&D and training to deploying and monitoring. Use cases include churn / acquisition modelling and other propensity models.

Likelihood to Recommend

If you're starting to build out your Data Science + ML/AI team this is the platform which will jump start you and get you from 0 to 1 much faster compared to doing things natively within the hyperscaler eco-system.

For very complicated use cases or where you need hundreds of models at a micro geo level the licensing may become cost prohibitive.

Use Cases and Deployment Scope

We use automodelling (typically OTV binary regression), EDA tools and deployments.

Likelihood to Recommend

Well suited to regression and forecasting.

Use Cases and Deployment Scope

We use DataRobot to generate Machine Learning models that inform the user experience on our website. The predictions are real-time. I have been most impressed with the simplicity in deploying models.

Likelihood to Recommend

DataRobot is great for data scientists to allow them to work faster. But the simplicity in creating models could hurt a company if someone doesn't understand the model.

Use Cases and Deployment Scope

I used Data Robot to design a machine learning algorithm that profiled employee's work environment and absenteeism behaviour (as well as other market factors) to determine if they matched the profile of those employees who had left before us. We were able to use this information to understand the emerging turnover risk of our employees across our various facilities, managers, states and tenures.

The result allowed us to target our HR initiatives, provide additional training and support to staff and managers, and implement out of the box solutions to newly discovered issues resulting in turnover. It also allowed us to confirm and quantify the impact of different drivers on turnover, which in turn let us prioritise our responses. Finally, we were able to use the models to estimate the impact on turnover and costs a change initiative might cause by looking at the historical impact of initiatives run by our individual sites and/or how difference between a variable had impacted turnover previously.

Having access to data scientists and project management staff to help design, understand, train and utilize, identify use cases and design the change process was the highlight of their service.

Likelihood to Recommend

Data Robot is a powerful tool for greatly reducing the time required to build powerful and accurate machine learning models. It then allows you to utilize these items.

It is probably most appropriate for organisations looking to get into data science and incorporate Machine learning and AI into their decision making. Having dedicated resources that can be upskilled is perfect, as the expertise and software provided allows for a big jump from willing to able.

For the to work effectively, organisations should really consider dedicating at least one resource to the ML and AI projects, and understsand that not every project will yield fruit. A lot of this is innovation and experimentation, so relying on data Robots insights in make or break situations is not recommended. You also need to manage expectations well as the data you have may simply not allow for a powerful model.

Finally, the organisation must be open to change, this has to exist in tandem with the above. If the organisation's key stakeholders don't want to change, all the insights in the world won't help. So a willingness and ability to change effectively is required to maximize ROI.

Use Cases and Deployment Scope

I use DataRobot for predictive modeling. I use this for forecasting and use its recommendation system. I also use DataRobot for automation, to know relevant parameters from the data, and to improve decision making. DataRobot is very useful, it improves our efficiency and productivity because of its automation process such as data processing and data engineering.

Likelihood to Recommend

DataRobot is well suited for generating models, such as the Bscore model, which is very important to the banking and financial industry. DataRobot provides insights and recommendations as to what are the relevant parameters for predicting the score of every customer based on their behavior. DataRobot also cut the time on making a model for forecasting. I use DataRobot for forecasting the probability of default using the ODR and linking it with economic indicators.

Use Cases and Deployment Scope

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.

Likelihood to Recommend

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.

Use Cases and Deployment Scope

This is used for building data models for scorecard monitoring in our department, Risk Management.

Likelihood to Recommend

It is best suited to be used by Data Analytics team, especially in data modelling. It saved a lot of time since there were already recommended model to choose from.

Use Cases and Deployment Scope

I am using datarobot to develop Application and Behavioural Credit Scorecards for the Bank. Develop credit risk models to be used for various business operations (i.e., Products, Credit, and Collections), such as cross-selling, credit limit selling, and collection strategy formulation. Develop credit risk models to elevate lending decision-making and enhance risk management at CIMB PH.

Likelihood to Recommend

Predictive Modeling. Using Datarobot, I was able to build accurate predictive models quickly. It is also very useful in shortlisting risk factors, it provides Feature associations to include only the most relevant features in final model to reduce complexity and improve interpretability.

Use Cases and Deployment Scope

Helping business partners optimize their marketing campaigns based on the strategic objectives of the specific campaigns.

Likelihood to Recommend

Well suited for companies with mature data sets to enable quick project creation. The product enables discovery of new features based on the impact to overall model. DataRobot is excellent at reducing time to market for modeling projects.