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 …
DataRobot
DataRobot
Starting at $0
View PricingOverview
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…
Recent Reviews
DataRobot for finance
We use automodelling (typically OTV binary regression), EDA tools and deployments.
DataRobot is a great ROI
We use DataRobot to generate Machine Learning models that inform the user experience on our website. The predictions are real-time. I have …
Excellent for moving from willing to able.
I used Data Robot to design a machine learning algorithm that profiled employee's work environment and absenteeism behaviour (as well …
DataRobot saves us time and effort, provides peace of mind.
I use DataRobot for predictive modeling. I use this for forecasting and use its recommendation system. I also use DataRobot for …
An ideal end-to-end AutoML solution and force multiplier for skeleton crews!
As Australia's largest radiology business, we use it as part of our sales and outreach program to identify referring doctors who we need …
Intelligent Tool for Data Modelling
This is used for building data models for scorecard monitoring in our department, Risk Management.
Risk Modeller's Assessment of DataRobot
I am using datarobot to develop Application and Behavioural Credit Scorecards for the Bank. Develop credit risk models to be used for …
DataRobot enables rapid prototyping, reducing time to market
Helping business partners optimize their marketing campaigns based on the strategic objectives of the specific campaigns.
Review of DataRobot from a non-IT person
I normally use it for preliminary model checking in order to get an idea to estimate the accuracy or error. This step normally consumes a …
Very good tool to accelerate your ML process!
We use it to accelerate the building and deployment of our ML platform in our context to solve problems for financial applications.
DataRobot provided a swift, powerful, and automatic way to implement large data project in parallel
The DataRobot has great cloud computing and multitasking power for feeding large quantity of data. There are time series, categorical, and …
DataRobot = Best AutoML Platform on the Market.
We use DataRobot for a variety of use cases, such as automated quoting, forecasting/inventory management, and automation of machinery …
DataRobot is an excellent way to jumpstart a machine-learning project
DataRobot builds machine-learning models to predict creditworthiness of bond issuers.
DataRobot delivers
DataRobot helps us make sense of a large amount of information. Trying to predict what's going to happen is always difficult, but with …
How DataRobot Differs From Its Competitors
Comprehensive Platform
It is VERY friction-less and you don't have to worry about stitching a bunch of services together as with the hyperscalers. It just works and is very comprehensive from Dev to Ops.
AI Solutions
Agent retention and growth. DataRobot's propensity models have impacted this KPI significantly.
AI Solutions
Highly regulated environment, which DataRobot helps with via robust modeling and explainability.
AI Solutions
Doing real-time predictions can sometimes be difficult, DataRobot makes this easy.
AI Solutions
We have a lot of challenges around the rapid change and unpredictable nature of health care regulations. Additionally we face workforce challenges and tight operating regulations. Having something that is able to help us reduce these things by understanding complex situations from a multitude of …
Comprehensive Platform
Working in the banking industry can be exceptionally challenging due to its sensitivity and fast-paced nature. Our analytics department shoulders a substantial workload as it handles vast amounts of data. Fortunately, DataRobot has played a pivotal role in alleviating this burden. DataRobot not …
AI Solutions
Working in the banking industry can be exceptionally challenging due to its sensitivity and fast-paced nature. Our analytics department shoulders a substantial workload, as it handles vast amounts of data. Fortunately, DataRobot has played a pivotal role in alleviating this burden. DataRobot not …
Comprehensive Platform
Yes. I would recommend using DataRobot for any new organisation that has a skeleton crew in Data Science and are very early in their technology maturity level. It removes the costs related to engineering and MLOps and allows the scientists to focus on target design and model review rather than …
AI Solutions
Patient data is highly sensitive and limits the use cases we can experiment on and deploy to DataRobot. I'm aware they offer some promises on privacy and security. For example, without more guarantees and clearer compliance measures, we won't be able to use it for clinical applications such as …
Comprehensive Platform
it will be very useful for one-stop shop for data processing and modelling. Since it is on cloud platform, it is also accessible anytime, anywhere and not anymore dependent on on-premise server which is more prone to access issues.
AI Solutions
Data modelling takes really a lot of time to do and Data robot provided platform to do it fast and accurate at the same time
Comprehensive Platform
Automated Machine Learning (AutoML). It automates machine learning workflow which enable me to build effective predictive models quickly and efficiently.
AI Solutions
Developing predictive models for credit risk assessment. DataRobot can help automate building credit scoring, identify fraudulent transactions, ultimately improving decision-making and reducing risks.
AI Solutions
There is a desire to quickly develop prototype modes and perform back testing validations to ensure the efficacy of the suggested model. DataRobot enables rapid prototyping to allow multiple people to provide feedback on the results. Sharing information across teams allows for improved feeback …
Comprehensive Platform
Time To Market improved a lot; we deliver new models faster. We can delegate some parts of the ML process to DataRobot itself, which is ideal since we are a small team. Moreover, we are less dependent on other teams since we don't have to manage servers and/or machines on our own. We don't loose …
AI Solutions
Being a small team, a lot of ML tasks are concentrated on very few people. In order to scale our ML platform, we needed to delegate efficiently some parts of the process, and we needed a good tool that could automate this, ideally with a first-API approach using Python. Datarobot fits this.
Comprehensive Platform
The AI platform serves a great repository for all kinds of projects for testing and tuning. The result comparison between different projects are good to follow.
AI Solutions
Having a lot of null values for certain households and datarobot could automatically fill it. Having huge feature space that needs high computing power to do the models efficiently.
Comprehensive Platform
Developing end-to-end automation for the business is fast and easy.
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 …
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 …
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 …
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.
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 …
AI Solutions
Establish 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 …
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.
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.
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.
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 …
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. …
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 …
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 …
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 …
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 …
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 …
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.
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 …
Comprehensive Platform
In general, it saves much time by providing a digital snapshot of your data. I believe refinement is still necessary, but it can save weeks of work.
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.
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.
Comprehensive Platform
I think the best improvement has been in the time saved. To build predictive models through the classic way (coding in Python or R) is very time consuming
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
Comprehensive Platform
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.
Time to Value
We were already using a trial, so the move from trial to full was instantaneous.
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
- 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%
Reviewer Pros & Cons
Verified User
Director in Information Technology
Real Estate Company, 1001-5000 employees
Verified User
Professional in Information Technology
Financial Services Company, 1001-5000 employees
Pricing
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…
Entry-level set up fee?
- No setup fee
Offerings
- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
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Features
Platform Connectivity
Ability to connect to a wide variety of data sources
7.1
Avg 8.5
- 6.1Connect to Multiple Data Sources(48) Ratings
Ability to connect to a wide variety of data sources including data lakes or data warehouses for data ingestion
- 5.8Extend Existing Data Sources(43) Ratings
Use R or Python to create custom connectors for any APIs or databases
- 8.4Automatic Data Format Detection(51) Ratings
Automatic detection of data formats and schemas
- 8.1MDM Integration(24) Ratings
Integration with MDM and metadata dictionaries
Data Exploration
Ability to explore data and develop insights
7.9
Avg 8.4
- 8Visualization(51) Ratings
The product’s support and tooling for analysis and visualization of data.
- 7.8Interactive Data Analysis(50) Ratings
Ability to analyze data interactively using Python or R Notebooks
Data Preparation
Ability to prepare data for analysis
7.7
Avg 8.2
- 7.4Interactive Data Cleaning and Enrichment(44) Ratings
Access to visual processors for data wrangling
- 7.5Data Transformations(49) Ratings
Use visual tools for standard transformations
- 8.1Data Encryption(26) Ratings
Data encryption to ensure data privacy
- 7.9Built-in Processors(42) Ratings
Library of processors for data quality checks
Platform Data Modeling
Building predictive data models
8.6
Avg 8.5
- 7.6Multiple Model Development Languages and Tools(45) Ratings
Access to multiple popular languages, tools, and packages such as R, Python, SAS, Jupyter, RStudio, etc.
- 9.3Automated Machine Learning(54) Ratings
Tools to help automate algorithm development
- 9Single platform for multiple model development(51) Ratings
Single place to build, validate, deliver, and monitor many different models
- 8.5Self-Service Model Delivery(50) Ratings
Multiple model delivery modes to comply with existing workflows
Model Deployment
Tools for deploying models into production
8.3
Avg 8.6
- 8.5Flexible Model Publishing Options(49) Ratings
Publish models as REST APIs, hosted interactive web apps or as scheduled jobs for generating reports or running ETL tasks.
- 8.2Security, Governance, and Cost Controls(43) Ratings
Built-in controls to mitigate compliance and audit risk with user activity tracking
Product Details
- About
- Integrations
- Competitors
- Tech Details
- Downloadables
- FAQs
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).
Comparisons
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Reviews and Ratings
(84)Attribute Ratings
Reviews
(1-4 of 4)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.
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.
75%
7.5
- Connect to Multiple Data Sources
- 100%10.0
- Extend Existing Data Sources
- 100%10.0
- Automatic Data Format Detection
- 100%10.0
- MDM Integration
- N/AN/A
85%
8.5
- Visualization
- 80%8.0
- Interactive Data Analysis
- 90%9.0
70%
7.0
- Interactive Data Cleaning and Enrichment
- 100%10.0
- Data Transformations
- 80%8.0
- Data Encryption
- N/AN/A
- Built-in Processors
- 100%10.0
80%
8.0
- Multiple Model Development Languages and Tools
- 70%7.0
- Automated Machine Learning
- 100%10.0
- Single platform for multiple model development
- 100%10.0
- Self-Service Model Delivery
- 50%5.0
45%
4.5
- Flexible Model Publishing Options
- 90%9.0
- Security, Governance, and Cost Controls
- N/AN/A
- 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
So far we like the results we have got from DataRobot, but the results need to be consistent for a long period of time before I can commit to a further purchase.
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
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).
62.5%
6.3
- Connect to Multiple Data Sources
- 90%9.0
- Extend Existing Data Sources
- 40%4.0
- Automatic Data Format Detection
- 60%6.0
- MDM Integration
- 60%6.0
35%
3.5
- Visualization
- 40%4.0
- Interactive Data Analysis
- 30%3.0
70%
7.0
- Data Transformations
- 50%5.0
- Built-in Processors
- 90%9.0
90%
9.0
- Multiple Model Development Languages and Tools
- 100%10.0
- Automated Machine Learning
- 90%9.0
- Single platform for multiple model development
- 90%9.0
- Self-Service Model Delivery
- 80%8.0
80%
8.0
- Flexible Model Publishing Options
- 70%7.0
- Security, Governance, and Cost Controls
- 90%9.0
- 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
DataRobot is embedded into our platform and we have still not fully used all it's abilities.
No
- Product Features
December 21, 2021
Analyst's take on DataRobot as an analytical accelerator
Verified User
Analyst in Finance and Accounting
Insurance Company, 51-200 employees
I am one of several analysts at our organization who uses DataRobot for predictive modeling in an insurance context. Several of us are all working on models that are subsets of a large data set that we are hoping to use to help with future pricing efforts.
- The breadth of models available to use is helpful and allows much more analytical power than programming them all yourself.
- The built-in variable diagnostics are helpful when testing large variable sets to see which perform the best.
- Many of the adjustments on the models are easy to use/it's easy to re-run and kick off new models as you want to try new things.
- Make it easier to add one feature to a feature list. select all, go to the overall data tab, then select the new ones and create a new list. Something like [adding] one variable or a selected set with an existing list and [creating] a new one.
- Easier access to project specs like target/offsets/etc. from the data tab
- switch to toggle on and off generation of feature impacts/effects when you start new models.
It is well suited for analysts like myself who are familiar with predictive modeling and understand some of the behind-the-scenes aspects but aren't to the point where they could program a predictive model by themselves from scratch. I think I've had the most success with it as an analytical accelerator. If you have no modeling experience or aren't familiar with some of the concepts, it will still work, but it could be a bit overwhelming/you might lack the knowledge to make intelligent business decisions with the results. On the opposite end, it can definitely help seasoned modelers who are able to do things from scratch themselves, but it can provide a hindrance if there are specific tweaks you want to make that aren't available in data robots or are two hard to decipher from the back end.
- Ability to enable accelerate analytical capability of the organization by allowing analysts who aren't able to model from scratch still produce high-quality predictive models with data robot.
- Ability to rapidly test large numbers of variables in models efficiently to figure out which works best.
- The connectivity and API's to other data sources/etc. integrate well once set up
60%
6.0
- Connect to Multiple Data Sources
- 80%8.0
- Extend Existing Data Sources
- 90%9.0
- Automatic Data Format Detection
- 70%7.0
- MDM Integration
- N/AN/A
80%
8.0
- Visualization
- 80%8.0
- Interactive Data Analysis
- 80%8.0
20%
2.0
- Interactive Data Cleaning and Enrichment
- N/AN/A
- Data Transformations
- N/AN/A
- Data Encryption
- N/AN/A
- Built-in Processors
- 80%8.0
80%
8.0
- Multiple Model Development Languages and Tools
- 80%8.0
- Automated Machine Learning
- 80%8.0
- Single platform for multiple model development
- 80%8.0
- Self-Service Model Delivery
- 80%8.0
N/A
N/A
- Flexible Model Publishing Options
- N/AN/A
- Security, Governance, and Cost Controls
- N/AN/A
- Without much exposure to the software, we were able to turn around and produce a model capable of helping make business decisions in ~2 weeks. That likely would have taken months had it needed to be created manually.
- It significantly helped our team be able to split out a large-scale modeling project and allow several analysts and data scientists to work simultaneously and with some help of integration to AWS/etc. was able to work well to spread out the modeling burden but allow it all to be combined back together fairly easily.
10
They are all connected to the analytics department. Some of our data and infrastructure folks were involved in the set-up and connectivity, but most of those using DataRobot were data scientists, actuaries, or data analysts.
1
- Analytical accelerator
- It worked as intended by allowing several people to work on a large scale predictive modeling project simulatenously.
- More data cleaning and processing in data robot itself vs elsewhere
If it was up to me, I would renew because it allows me to do a lot more predictive modeling than I am able to do from scratch/without learning additional things.
August 17, 2018
A Review of DataRobot.
Verified User
Manager in Quality Assurance
Civil Engineering Company, 51-200 employees
We are using DataRobot as a department-wide software system for analytics on predictability on the Information Technology sector of our firm. Mainly we are utilizing the program for best practices in order to assist in company-wide decision making. It has addressed various manpower issues by yielding a level of automation that eases use of machine learning tasks, basically by displaying helpful predictive models.
- DataRobot helps, with algorithms, to analyze and decipher numerous machine-learning techniques in order to provide models to assist in company-wide decision making.
- Our DataRobot program puts on an "even playing field" the strength of auto-machine learning and allows us to make decisions in an extremely timely manner. The speed is consistent without being offset by errors or false-negatives.
- It encompasses many desired techniques that help companies in general, to reconfigure in to artificial intelligence driven firms, with little to no inconvenience.
- The importance of realizing that most software programming in the Predictive Analysis genre is not 100% ideal cannot be overstated. It's tough to locate a program that would fulfill every need of every business type and size. Though DataRobot is about as close as it gets, it may not be for every industry.
- Though DataRobot helps to capture six sigma techniques, knowledge, and expertise of the best data scientists in the nation, it may end up causing rifts in intercompany personnel due to fear of job loss on a long term scale.
- Though fairly priced for a firm of our size and capability, it may be out of market reach for smaller companies at this point. It's important for every firm to understand exactly what they need and can afford.
DataRobot is equipped to serve both cloud computing and on-premise work. Its comprehensive cloud module, channeled through Amazon sustains highly flexible machine learning programs. Lower than average costs are provided via cloud networking because there is no need to install hardware and the additional pricing that comes along with that. DataRobot assists in eliminating hassle by offering various methods of deployment in regard to predictive modeling. The program may not be appropriate for smaller startups of 20 or fewer employees, mainly because the exportable prediction code, and native batch scoring may not translate as well to a smaller firm.
- DataRobot can run multiple experiments at the same time. This helps to minimize time spent on any given experiment.
- DataRobot helps to get rid of bottlenecks by yielding various ways to enact completed models of prediction.
- I consider the Return on Investment high. APIs for real-time scoring have saved us many dollars and time.
We started off using BigML. A positive about BigML would be that it doesn't require files on your local drive. You just need an internet connection and API allows the user to do anything he or she needs (including model deployment and prediction). We ended up with DataRobot mainly, initially because BigML doesn't provide offline support like other open-source programming does. In the long run DataRobot was much more cost effective as well.
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Most of the employees here are analytics strategists. The best tuning of models along with machine learning and generation of reports is tucked in to the most advanced features. Our strategists view the data preparation package, (which has a lot of power) and integrate the predictive modeling via automation. The work-flow is easy with the DataRobot API.
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Support for DataRobot requires a rapid response time. Critical yet effective machine learning, for us, needs a response where we are never left in the wait with an issue. Our in house personnel typically can have a response time of thirty minutes, and he or she is uniquely attune to very specific cases. We appreciate the training via DataRobot, in regard to our own response team.
- Automation on a machine-learning platform eases the most mundane tasks that an analyst may have to do in order to make decisions.
- DataRobot has a platform that is designed to be less error-prone and faster than other programming, thereby addressing the shortage of data scientists available in the market.
- Predicative modeling is utilized in presentation of new data in order to make probability-based predictions in the market. These use cases are based on the given patterns.
- Self-service machine learning is one way we gauge success. We have found that even non-analysts in our firm are more than capable of undertaking intense artificial intelligence projects. We did not expect this.
- We were pleasantly surprised by how accessible, the Customer Facing Data Scientists were/are with DataRobot. Very present for email or phone conversation.
- Scope of work and framing issues have been innovated for us by data science projects as well as great, above-standard communication.
- Increased organizational complexity and pronounced artificial intelligence in the form of predictive modeling.
- We are interested in the acceleration packages, as well, in order to better educate most of our staff.
- Our end game here is to encompass this very pervasive software and fundamentally transform our current models, in a way that positively impacts earnings.
DataRobot presents a machine-learning platform designed by data scientists from an array of backgrounds, to construct and develop precise predictive modeling in a fraction of the time previously taken. The tech invloved addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics. DataRobot utilizes parallel processing to evaluate models in R, Python, Spark MLlib, H2O and other open source databases. It searches for possible permutations and algorithms, features, transformation, processes, steps and tuning to yield the best models for the dataset and predictive goal.