How does DataRobot BI & Analytics score on different parts?
In our survey we also judged all relevant products of DataRobot software. More than 720 evaluation criteria were examined. The bar chart below illustrates the strengths and weaknesses of DataRobot platform, in general terms. Please note that Passionned Group is 100% independent of the suppliers in our guide. We do not sell licenses, we do not make deals or have any relationship with the vendor. Among other things, we help and advise companies in the proper selection of BI tooling.
Figure 1: Scorecard of the BI provider DataRobot. A top supplier can get a maximum of 100%. Source: the BI & Analytics Guide 2023. Do you want to take a deep dive into our research design? Click here to download this guide.
The DataRobot analysis was conducted by tapping into a lot of public big data and from there it was analyzed in-depth. More than 2,180 documents were analyzed for this vendor. In this analysis process both algorithms as the subject matter expertise of a BI consultant played an important role in drawing conclusions.DataRobot BI & Analytics in our BI & Analytics Guide 2023. In our 100% vendor-independent BI & Analytics Guide we have collected all the ins and outs of DataRobot BI & Analytics for you.
DataRobot and their complete BI & Analytics product portfolio
The software company DataRobot carries (a minimum of) 5 products in the realm of BI & Analytics. Based on relevance we list the products below:
What is DataRobot platform?
We do not display here all the features but, in this paragraph, we describe DataRobot platform, including some of its features and any related products. This product group consists of DataRobot Artificial Intelligence, DataRobot Core, DataRobot AutoML and DataRobot MLOps. This product / group of products can be characterized by the following characteristics:
- artificial intelligence
- AI
- artificial intelligence > machine learning
- artificial intelligence > data science
- BI infrastructure > scalability > cloud platform
- BI infrastructure > Application Programming Interface
- BI infrastructure > API
- BI infrastructure > scalability > Amazon Web Services
- BI infrastructure > authentication
- artificial intelligence > machine learning > automated machine learning
Are you now curious about all features (100+) of DataRobot platform? Download the BI & Analytics Guide™ 2023 here.
Are you considering hiring an expert in DataRobot platform?
Do you want to hire a freelance DataRobot platform developer who can help you get started and implement an DataRobot platform application? Or do you want to implement an application for one of the related products like DataRobot Artificial Intelligence? Our interim specialists are happy to help. Indeed, hiring DataRobot platform developers is not always expedient. Leave a message here and we will explore the possibilities of cooperation with you.
What is DataRobot Artificial Intelligence?
Other names by which this software product is known: DataRobot AI
In this section, we provide a description of DataRobot Artificial Intelligence, including some of its features and any related products. The product DataRobot Artificial Intelligence can be best characterized by the following characteristics:
- AI
- artificial intelligence > machine learning
- artificial intelligence > algorithms
- artificial intelligence > data science
- BI infrastructure > scalability > cloud platform
- artificial intelligence > natural language processing > natural language
- analytics > advanced analytics > predictive maintenance
- artificial intelligence > cognitive computing
Are you now curious about all elements (100+) of DataRobot Artificial Intelligence? Download the BI & Analytics Guide™ 2023 here.
What is DataRobot Core?
In this paragraph, we give you insight in the key behaviors of DataRobot Core, including some of its features and any related products. DataRobot Core can be characterized by the following characteristics:
- artificial intelligence > machine learning
- artificial intelligence > data science
- artificial intelligence > machine learning > machine learning models
- decision management > decision intelligence
- BI infrastructure > scalability > cloud platform
- BI infrastructure > Application Programming Interface
- data governance > data management > data preparation
- artificial intelligence > machine learning > automated machine learning
- data discovery > time series
Do you want to know everything about all properties (100+) of DataRobot Core? In that case open the BI & Analytics Guide™ 2023 here.
What is DataRobot AutoML?
We do not display here all the features but, in this paragraph, we describe the key elements of DataRobot AutoML, including some of its features and any related products. DataRobot AutoML can be best characterized by the following features:
- artificial intelligence > machine learning
- AI
- artificial intelligence > ML
- BI infrastructure > scalability > cloud platform
- data governance > data management > data preparation
- artificial intelligence > machine learning > automated machine learning
- BI infrastructure > scalability > AWS
- artificial intelligence > data science
- robotic process automation
Do you want to know the intricacies of all properties (100+) of DataRobot AutoML? Open the BI & Analytics Guide™ 2023 here.
What is DataRobot MLOps?
We do not display here all the features but, in this paragraph, we report the (main) characteristics of DataRobot MLOps, including some of its features and any related products. This product can be characterized by the following properties:
- artificial intelligence > machine learning
- AI
- artificial intelligence > ML
- business intelligence > reporting
- artificial intelligence > machine learning > machine learning models
- artificial intelligence > machine learning > automated machine learning
- artificial intelligence > Python
- BI infrastructure > repository
- artificial intelligence > R
- BI infrastructure > SDK
Are you curious about all elements (100+) of DataRobot MLOps? Then order the BI & Analytics Guide™ 2023 here.
Recent innovations of DataRobot platform-tools and the version history
Recently, we see a positive trend in terms of BI & Analytics functionality. The latest innovations are in the areas of data discovery > analysis > financial analysis, data connectivity > Google Analytics and data governance > data lineage > lineage capabilities.
We reviewed DataRobot’s current releases of its complete product portfolio. Below you can see the structure of the history of the different versions of the various BI & Analytics products of DataRobot:
- DataRobot AutoML: 7.1
- DataRobot MLOps: 8 7.1 7
- DataRobot platform: 8 7.3 7.2 7.0 7 6 5 3.0.2
Behind each product we show the version numbers, the most recent versions are mentioned first.
What are the licensing costs of DataRobot Artificial Intelligence, DataRobot Core and DataRobot AutoML?
It is difficult to determine exactly what a license of DataRobot Artificial Intelligence, DataRobot Core and DataRobot AutoML costs because it depends on the country, the number of users (or the number of CPUs in the case of server software), the connectors to data sources, and at what point in the year you request a quote. If you do this a few weeks before the end of DataRobot’s fiscal quarter, you may be in for a decent discount. In addition, nowadays it is recommended running the software in the cloud. You then only pay for what you actually use in resources. The purchase cost of DataRobot Artificial Intelligence, DataRobot Core and DataRobot AutoML may not be the most important costs, but maintenance and support do show up in your budget every year.
What makes DataRobot BI & Analytics worth watching
In our study, we see that DataRobot in the field of BI & Analytics software has a number of specific features which are worth weighing in a tool selection. This makes DataRobot platform more or less unique: generative pre-trained, deep learning algorithms, decision flow, risk modeling and linear regression model.
The advantages and disadvantages of DataRobot platform
Figure 14: Tag cloud with the strength-weakness analysis of DataRobot BI & Analytics
In the following sections, we describe all the advantages and disadvantages of DataRobot BI & Analytics, DataRobot Artificial Intelligence, DataRobot Core and DataRobot AutoML, et cetera. There is momentum, because: DataRobot can currently work on developing features that meet specific customer needs at this time (such as support for KPI, CSV, embedded analytics, Linux, OLAP, ODBC, conditional formatting, caching, cube and scalability). It may also be that a feature has not yet been adequately described.
We value your opinion
Leave a review about DataRobot BI & Analytics here. Your findings may then be taken into account and contribute to a better, even more balanced assessment of DataRobot platform.
1. DataRobot Artificial Intelligence
The vendor DataRobot has a good score in our independent BI & Analytics survey of the theme ‘Artificial Intelligence’, given that they score 55% on this, relative to other vendors. We looked at the following criteria, among others: data science, Python, data mining, algorithms, natural language processing and cognitive services. In doing so, we investigated the following four products: DataRobot platform, DataRobot AutoML, DataRobot Artificial Intelligence and DataRobot Core. In total, we examined 181 criteria in this category. Are you planning to specialize further in the topic ‘Artificial Intelligence’? Then download here our BI & Analytics Guide.
2. DataRobot Decision Management
The company has a moderate score in our independent BI & Analytics survey of the theme ‘Decision Management’ with a score of 36%, compared to other vendors. We considered the following factors: performance management, decision support, decision-making platform, decision intelligence, decision optimization, enterprise decision management and real-time decisioning. In total, we examined 30 criteria within this section. Would you like to delve further into the topic ‘Decision Management’? Then download here our BI & Analytics Study. Or take a deep dive in the following content:
3. DataRobot BI Infrastructure
The vendor DataRobot has a moderate performance in our recently updated, independent BI & Analytics study on the subject ‘BI Infrastructure’, given that they score 34% on this, compared to other vendors. We looked at the following criteria, among others: authentication, infrastructure, repository, embedded analytics, scalability and high availability. In total, we examined 162 selection criteria within this main theme. Would you like to delve further into the topic ‘BI Infrastructure’? Then download here our BI & Analytics Guide 2023.
4. DataRobot Big Data
The company has a moderate rating in our study on the section ‘Big Data’ with a score of 32%, relative to other vendors. We used the following selection criteria: streaming and unstructured data. In total, we examined 59 selection criteria within this main theme. Would you like to go into more depth with the topic ‘Big Data’? Then download here our BI & Analytics Guide. Or take a deep dive in the following content:
5. DataRobot Data Governance
DataRobot has a moderate rating in our objective BI & Analytics survey on the subject ‘Data Governance’. The company scores 30% on this topic, compared to other vendors. The following criteria were used: data management, data quality, data catalog, data encryption, data lineage and data acquisition layer. In total, we examined 91 features within this discipline. Are you planning to specialize further in the topic ‘Data Governance’? Then download here our BI & Analytics Guide.
6. DataRobot Data Connectivity
DataRobot has a poor score in our 100% vendor-independent BI & Analytics survey on the section ‘Data Connectivity’. The score amounts to 28%, relative to other vendors. The following criteria were used: Sharepoint, connectivity, native, Teradata, Google Analytics and Amazon Redshift. In total, we examined 91 criteria within this section. Are you excited about the topic ‘Data Connectivity’? Then download here our BI & Analytics Study.
7. DataRobot Analytics
The vendor DataRobot has a poor score in our objective BI & Analytics survey on the section ‘Analytics’. The score amounts to 27%, relative to other vendors. We considered the following factors: analytics platform and customer analytics. In doing so, we investigated the following products: DataRobot platform. In total, we examined 130 criteria within this section. Would you like to delve further into the topic ‘Analytics’? Then download here our BI & Analytics Study 2023.
8. DataRobot Real-time Analytics
The company has a poor score in our objective BI & Analytics survey on the subject ‘Real-time Analytics’, given that they score 27% on this, relative to other vendors. We used the following selection criteria: real-time, real-time data, data ingestion, near real-time, real-time insights and live connection. In total, we examined 19 selection criteria within this main theme. Would you like to go into more depth with the topic ‘Real-time Analytics’? Then download here our BI & Analytics Guide 2023.
9. DataRobot Self-service BI
The company has a poor performance in our 100% vendor-independent BI & Analytics survey of the theme ‘Self-service BI’. The company scores 23% on this topic, compared to other vendors. We considered the following factors: self-service data preparation, self-service reporting, self-service data discovery, self-service data analytics, self-service data visualization and self-service data exploration. In total, we examined 14 features within this discipline. Would you like to go into more depth with the topic ‘Self-service BI’? Then download here our BI & Analytics Guide.
10. DataRobot Business Intelligence
DataRobot has a poor score in our independent BI & Analytics survey on the subject ‘Business Intelligence’, given that they score 21% on this, relative to other vendors. The following criteria were used: reporting, business intelligence platform, enterprise business intelligence and business process monitoring. In total, we examined 73 features within this discipline. Would you like to delve further into the topic ‘Business Intelligence’? Then download here our BI & Analytics Guide. Or take a deep dive in the following content:
11. DataRobot Data Discovery
DataRobot has a poor performance in our study on the subject ‘Data Discovery’. The score amounts to 17%, compared to other vendors. We looked at the following criteria, among others: time series, data visualization, notifications and standard deviation. In total, we examined 398 selection criteria within this main theme. Would you like to become more proficient in the topic ‘Data Discovery’? Then download here our BI & Analytics Guide.
12. DataRobot Performance Optimization
DataRobot has a poor rating in our 100% vendor-independent BI & Analytics survey on the section ‘Performance Optimization’ with a score of 11%, compared to other vendors. We considered the following factors: data pipelines, materialized views, quantum computing, cached data and cache settings. In total, we examined 29 aspects in this category. Are you excited about the topic ‘Performance Optimization’? Then download here our BI & Analytics Guide 2023.
13. DataRobot Data Integration
The vendor DataRobot has a poor performance in our objective BI & Analytics survey on the section ‘Data Integration’, given that they score 11% on this, relative to other vendors. The following criteria were used: data warehousing and data virtualization. In total, we examined 76 criteria within this section. Would you like to go into more depth with the topic ‘Data Integration’? Then download here our BI & Analytics Guide.
14. DataRobot Mobile Business Intelligence
DataRobot has a poor rating in our objective BI & Analytics survey on the subject ‘Mobile Business Intelligence’. The score amounts to 5%, compared to other vendors. The following criteria were used: Android and mobile server. In total, we examined 10 features within this discipline. Would you like to delve further into the topic ‘Mobile Business Intelligence’? Then download here our BI & Analytics Study.
15. DataRobot Multidimensional Models
The vendor DataRobot has a poor rating in our study on the subject ‘Multidimensional Models’. The score amounts to 0%, compared to other vendors. We considered the following factors: ROLAP and tabular data models. In total, we examined 14 selection criteria within this main theme. Would you like to become more proficient in the topic ‘Multidimensional Models’? Then download here our BI & Analytics Guide.
Want to know more? Then order the BI & Analytics Guide™ 2023 here
In which sectors is DataRobot BI & Analytics most active?
In our 100% vendor-independent BI & Analytics survey about, we also looked at which industries a supplier moves around. These are the industries where DataRobot is most frequently used: automotive, banking, biotech, energy, fashion, health care, higher education, insurance, manufacturing, public sector, retail, steel, universities and utilities.
DataRobot software is most used by…
The BI & Analytics software from DataRobot is most often mentioned in combination with the following functions: business analysts, data scientists, information steward and marketers.
Hire a qualified DataRobot developer
Training and incompany training DataRobot BI & Analytics
We facilitate various training courses in the field of BI & Analytics but can also provide specific DataRobot training, for example as incompany. For example, you can think about the following software: DataRobot Artificial Intelligence, DataRobot Core and DataRobot AutoML. Of course we color such a training with the ideas of the intelligent, data-driven organization.
In conclusion: DataRobot platform scores moderately
DataRobot has a minimal product portfolio with which it scores moderately in our BI & Analytics survey. DataRobot BI & Analytics innovates (approximately) at an average rate of more than 15 features per year, is active (for now) in lots of different sectors, and specializing in artificial intelligence.
About Passionned Group
Passionned Group specializes in 100% independent BI & Analytics consulting and the implementation of BI & Analytics solutions. We help large and small governments and businesses to advance as intelligent, data-driven organizations.
