Data Science and MLOps
Operationalize to accelerate the AI lifecycle
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Cloud Pak for Data 4.7 is here
How Data Science and MLOps is used
Data access, prep and pipelines Right data, at the right time for the right user Use fairness scores to improve bias reduction. Provide complete views of quality, secured data for permission-based, self-service access. Try it now

Building and deploying Accelerate and scale production Build and deliver models using MLOps to decrease costly human errors, improve workload efficiency and speed time to analytic insights. Try it now

Monitoring and retraining Proactively detect and correct Automate the detection of model degradatiom, drift and bias for model retraining and the need to retire Try it now
Benefits of Data Science and MLOps Make trusted data available

Empower data scientists with self-service access to the right data for their project.

Speed time to AI insights

Build and move models into production quicker using automated tools and delivery.

Eliminate manual processes

Automate error prone, time intensive tasks so data scientists can focus on value-add initiatives.

Connect stakeholders

Automate collaboration between the growing number of stakeholders with automated workflows

Monitor, track and retrain AI models

Ensure models work effectively and meet today’s ethical risk and regulatory concerns.

Capabilities Data Science and MLOps documentation Integrated visual tooling

Prepare data quickly and develop models visually with IBM SPSS Modeler in IBM Watson® Studio.

Model training and development

Build experiments quickly and enhance training by optimizing pipelines and identifying the right combination of data.

Extensive open source frameworks

Bring your model of choice to production, track and retrain models using production feedback.

Embedded decision optimization

Combine predictive and prescriptive models to optimize decisions. Create and edit models in Python, in OPL or with natural language.

Model management and monitoring

Monitor quality, fairness and drift metrics. Select and configure deployment for model insights. Customize model monitors and metrics.

Included solutions
IBM Watson® Studio

Simplify model production from any tool, automate model retraining and monitor for accuracy.

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IBM Knowledge Catalog

Automate metadata collection and policy management.

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News and events IBM Cloud Pak for Data 4.7 now available

Version 4.7 of Cloud Pak for Data is now available. Check out what's new.

Read the release notes
IBM acquires Databand.ai

Learn more about the IBM acquisition of Databand.ai, which enables a more proactive approach to data reliability.

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IBM Cloud Pak for Data Express

You get a set of three pre-built, pre-sized offerings designed to address problems in cataloging, analyzing and integrating data. Check out the low-cost options for data fabric use cases.

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Resources Deep learning workloads

Optimize deep learning with IBM Cloud Pak for Data

Data management

See which topics are most pressing and how a data fabric can help

Explainable AI

Learn how to break down barriers to enterprise AI on IBM Cloud Pak for Data

Data Science and MLOps: An overview

Learn about common Data Science and MLOps challenges and how IBM solves them through IBM Watson Studio

A data and AI platform-in-a-box

IBM Watson Studio recognized as Leader in IDC's Worldwide Machine Learning Operations Platforms 2022 Vendor Assessment

Take the next step

Get started with a free trial of IBM Cloud Pak for Data or book a consultation with an IBM expert to discuss how it can advance your specific business needs.

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More ways to explore Resources Documentation Partners