Innovate - Scale - Accelerate

Transform your data into tangible business value with the latest, most flexible and open technology. Enable your data scientists, data engineers, machine learning engineers, and analysts to collaborate with the best-in-class open source tools and visual tools, along with the most flexible and scalable deployment options. 

Combine machine learning models with advanced prescriptive modeling to optimize complex business decisions. Use fast visual modeling capabilities without coding, advanced data preparation capabilities, and automatically handle common data quality issues. Bring your analytics to the data behind your firewall, and easily incorporate cloud application data and sources.

Get the latest insights from Gartner

Data Science Strategies webinar – featuring Gartner

View the video to learn about:

  • Considerations for building a data science team
  • Important capabilities for tools and platforms
  • Keys to success for data science projects
  • How to get started

2017 Gartner Magic Quadrant for Data Science Platforms

Read the report to learn:

  • Why data science, analytics, and machine learning are engines of the future
  • How 16 providers of data science platforms compare
  • Why IBM is recognized as a leader

Capabilities

Predictive Analytics

Predictive analytics brings together advanced analytics capabilities, spanning ad-hoc statistical analysis, predictive modeling, data mining, text analytics, optimization, real-time scoring and machine learning. These tools help organizations discover patterns in data and go beyond knowing what has happened to anticipating what is likely to happen next.

Prescriptive Analytics

Prescriptive analytics helps organizations make better decisions and recommend the best course of action, whether you want to decide on a configuration, a design, a plan, or a schedule. This is done by optimizing trade-offs between business goals while considering business constraints on available resources.

Machine Learning

Infuse continuous intelligence into your enterprise applications with an end-to-end platform for developing and deploying data science projects quickly. IBM has the leading data science platform that allows you to easily collaborate across teams, use the top open source tools and scale at the speed your business requires.

Get your free copy of Machine Learning for Dummies

Chapters include:

  • Putting machine learning in context
  • Approaches of machine learning
  • Getting started with a strategy
  • Understanding machine learning techniques
  • Tying machine learning methods to outcomes
  • Applying machine learning to business needs

Resources

Data science is a team sport

Working together, learn how the data science team can outthink today’s challenges and problems to create new opportunities and possibilities for tomorrow.

Machine learning is about your data and deployment

Dinesh Nirmal explains how your data can help you build the right cognitive systems to learn about, reason with, and engage with your customers.

Spark Technology Center

In downtown San Francisco, engineers, Apache Spark Committers, and designers contribute to Apache Spark and design optimal UX experiences for people using Spark-based applications. 

A glimpse inside the mind of a data scientist

Find out what data scientists really think about their critical role in data science.

Customer Success

AMC Networks

Analyzing big data in seconds unlocks never-before-seen capabilities, helping to win new viewers and advertisers.

XO Communications

Take control of customer satisfaction by using predictive analytics to embed a deeper understanding of customers into operations.

Grupo Boticário

Predictive analytics helps the world’s largest perfumery and cosmetics franchiser understand what customers want, before they even know they want it—enabling smarter sales, marketing and production planning.