Data science tools and solutions
Uncover patterns and build predictions using data, algorithms, machine learning and AI techniques
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Harness the power of data science

Practicing data science comes with challenges. It comes with fragmented data, a short supply of data science skills, and various tools, practices, and frameworks to choose from run with rigid IT standards for training and deployment. It's also challenging to operationalize ML models with unclear accuracy and difficult-to-audit predictions.

Using IBM data science tools and solutions, you can accelerate AI-driven innovation with:
- An intelligent data fabric
- A simplified ModelOps lifecycle
- The ability to run any AI model with a flexible deployment
- Trusted and explainable AI

In other words, you get the ability to operationalize data science models on any cloud while instilling trust in AI outcomes. Moreover, you'll be able to manage and govern the AI lifecycle with ModelOps, optimize business decisions with prescriptive analytics and accelerate time to value with visual modeling tools.


Train, validate, tune and deploy foundation and machine learning models, with ease

The full impact of AI can only be achieved when AI can be trusted. Learn more about MLOps and trustworthy AI for data leaders.


Why IBM for data science AI lifecycle management

Scalable, integrated data science platform with capabilities spanning the full AI and ML lifecycle

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Modern data science technology

Prediction and optimization technologies for better decision-making

Read the business guide (2.6 MB)
ModelOps approach

Operationalizing AI models in sync with DevOps for faster ROI

Explore ModelOps

Use cases

Personalize experiences using predictive insights Augment human intelligence with machine insights at speed and scale, driving better customer experiences. Read an example

Integrate AI into decision making Power decision intelligence on a multicloud platform with decision optimization, visual modeling and open source data science tools. Watch an example (03:22)

Debias and safeguard AI with explainability Use explainable AI and model monitoring so you can trust model decisions and mitigate risks of AI bias and fraud. Read an example

Related data science tools Build and scale trusted AI on any cloud

Automate the AI lifecycle and accelerate time to value with an open, flexible architecture.

Connect timely targeted data to the right people from anywhere

Collect, organize and analyze data across any cloud with a fully integrated data and AI platform.

Uncover insights to solve business and research problems

Extract actionable insights from your data with a user-friendly interface and robust procedures.

Optimize decision making to improve business outcomes

Gain prescriptive analytics capabilities to optimize decisions with a family of products.

IBM a Leader in the Gartner 2021 Magic Quadrant for Data Science and Machine Learning

Case studies


Next steps
ESG Technical Validation

Request the report on IBM Watson Studio and IBM Machine Learning.

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Talk to a data science professional

Contact a representative and get help with questions on how to start your journey.