How Data Science and MLOps is used

Data access, prep and pipelines

Data pipelines dashboard

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.

Building and deploying

Deploying models using MLOps dashboard

Accelerate and scale production

Build and deliver models using MLOps to decrease costly human errors, improve workload efficiency and speed time to analytic insights.

Monitoring and retraining

Auto detect error dashboard

Proactively detect and correct

Automate the detection of model degradatiom, drift and bias for model retraining and the need to retire

Benefits of Data Science and MLOps

Make trusted data available

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

Speed time to AI insights

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

Eliminate manual processes

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

Connect stakeholders

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Automate collaboration between the growing number of stakeholders with automated workflows

Monitor, track and retrain AI models

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

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

Capabilities of IBM Data Science and MLOps Solutions

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.

Get the trial at no cost

Operationalize to accelerate the AI lifecycle

Included solutions

IBM Watson® Studio

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

IBM Watson® Knowledge Catalog

Automate metadata collection and policy management.


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 though IBM Watson Studio