Data Science and Machine Learning Platforms
Data science and machine learning platforms provide software to build, customize and deploy AI models using various techniques. Data science, machine learning and AI leaders need to select platforms with awareness of AI agents enabling autonomous and interactive workflows and applications.
Market Definition
Gartner defines a data science and machine learning platform as an integrated set of code-based libraries and low-code tooling. These platforms support the independent use and collaboration among data scientists and their business and IT counterparts, with automation and AI assistance through all stages of the data science life cycle, including business understanding, data access and preparation, model creation and sharing of insights. They also support engineering workflows, including the creation of data, feature, deployment and testing pipelines. The platforms are provided via desktop client or browser with supporting compute instances or as a fully managed cloud offering.
Data science and machine learning (DSML) platforms are designed to enable a broad range of users to develop and apply a comprehensive suite of predictive and prescriptive analytical techniques. Leveraging data from distributed sources, code-first and low-code interfaces, and native machine learning and generative AI (GenAI) capabilities, these platforms enhance and automate decision making across an enterprise. They offer a range of proprietary and open-source tools to enable data scientists and domain experts to identify patterns in data that can be used to forecast financial metrics, understand customer behavior, predict supply and demand, and many other use cases. Models can be built on all types of data, including tabular data, images, video and text, for applications that require computer vision or natural language processing.
The supported machine learning techniques range from classic regression and decision trees to more complex deep learning, and reinforcement learning and GenAI. The models built using these techniques can be used for tasks within business processes, such as credit scoring, churn prediction, predictive maintenance, recommendation and image classification.
Organizations that use DSML platforms can significantly reduce the cycle time and barriers to entry for creating predictive and prescriptive models, generating insights, and distributing results. These platforms enable collaboration and reuse of assets across multiple teams and departments, as well as the orchestration of workloads to handle high volumes of data. They also provide consistent and reproducible training and development environments that establish lineage between data, code, and model assets, enhancing data scientists’ productivity. Additionally, low-code, natural language interfaces and AI assistance enable domain experts and business users to create predictive models with simple interactions. DSML platforms support MLOps practices such as deploying models in production, orchestrating both batch and real-time workloads, and ongoing monitoring of model metrics and compliance.
Report 2025
Here is a summary of the vendors featured in the Gartner magic quadrant 2025 report.
For the full analysis and detailed insights, you can read the report
here
and view the magic quadrant graphic
here.
| Market Status | Market Vendor |
|---|---|
Leader |
Databricks |
Leader |
|
Leader |
Amazon Web Services |
Leader |
Microsoft |
Leader |
Dataiku |
Leader |
DataRobot |
Leader |
IBM |
Leader |
Altair |
Visionary |
SAS |
Visionary |
Snowflake |
Visionary |
Domino Data Lab |
Visionary |
Cloudera |
Visionary |
H2O.ai |
Niche Player |
Alteryx |
Niche Player |
MathWorks |
Challenger |
Alibaba Cloud |
Report 2024
Here is a summary of the vendors featured in the Gartner magic quadrant 2024 report.
For the full analysis and detailed insights, you can read the report
here
and view the magic quadrant graphic
here.
| Market Status | Market Vendor |
|---|---|
Leader |
Databricks |
Leader |
Microsoft |
Leader |
|
Leader |
Amazon Web Services |
Leader |
Dataiku |
Leader |
Altair |
Leader |
SAS |
Leader |
DataRobot |
Visionary |
H2O.ai |
Visionary |
Cloudera |
Visionary |
Domino Data Lab |
Niche Player |
Alteryx |
Niche Player |
KNIME |
Niche Player |
MathWorks |
Niche Player |
Posit |
Niche Player |
Anaconda |
Challenger |
Alibaba Cloud |
Challenger |
IBM |