What is IBM Cloud Pak for Data?
IBM Cloud™ Pak for Data (formerly IBM Cloud Private for Data) is a new kind of data and analytics platform with built-in governance. It simplifies and unifies how you collect, organize and analyze data to accelerate the value of data science and AI. This multicloud platform delivers a broad range of core data microservices, with the option to add more from a growing services catalog. Experience greater flexibility, security and control, and the benefits of the cloud without having to move your data.
IBM Cloud Pak for Data features
Single, unified platform
Speed time to value with a single platform that integrates data management, data governance and analysis for greater efficiency and improved use of resources. Enable self-service collaboration across teams.
Industry-leading data virtualization
Query data easily and more securely across multiple sources, on cloud or on premises. Exploit the combined processing power of those sources for massive query acceleration and achieve the speed and scalability your business needs for today's and tomorrow’s workloads.
Built-in data governance
Efficiently respond to changing regulations with embedded, sophisticated governance capabilities; these include automated discovery and classification of data, masking of sensitive data, data zones and data lifecycle management.
AI-ready
Manage end-to-end data workflows to help ensure that data is easily accessible for AI. Make sure that your data is high-quality to deliver accurate, automated insights and decisions. Seamlessly build and manage machine learning models across development and production in a collaborative environment.
Cloud-native agility
Accelerate application development and deployment with a multicloud data platform that is agile, resilient and portable. Benefit from Kubernetes containerization to provision and scale services in minutes, instead of months, inside a more secure, governed environment.
Extensible APIs and ecosystem
Use best practices to your advantage to accelerate implementations and deliver significant business value. With IBM Cloud Pak for Data, benefit from built-in models and accelerators for various industries including finance, insurance, healthcare, energy, utilities and more.
Industry Accelerators
Benefit from a broad ecosystem of complementary hardware, software and services through a growing service catalog. Provision preferred data services flexibly and rapidly and customize data workflows to your individual needs.
Continuous intelligence
Develop real-time streaming applications and deliver continuous intelligence across your business. With IBM Streams on IBM Cloud Pak for Data, you can enable continuous and rapid analysis of massive volumes of data in motion or at rest. This can help you gain business insights faster and make more informed decisions.
Deployment options
Hyper-converged system
Simplify deployment and management with a hyper-converged system delivering the IBM Cloud Pak for Data platform in a pre-built private cloud.
Private cloud
Make use of Kubernetes architecture and microservice design for maximum flexibility while keeping data secure behind the firewall.
Public cloud
IBM Cloud Pak for Data runs on Amazon Web Services, Azure, Google and more, so you can bring your new Data and AI platform to your cloud partner of choice.
On-premises
For customers with on-premises data centers, install IBM Cloud Pak for Data and see what the new cloud data platform can do for you.
What clients and analysts are saying
"It's a very exciting product. You have a lot of things that a lot of different companies are doing, molded into one technology suite."
-James Wade, Director of Application Hosting, Guidewell
"With IBM Cloud Private for Data, IBM has pre-integrated capabilities that allow clients to be productive in a week or less."
-Leader in The Forrester Wave: Enterprise Insight Platforms Q1 2019
“Recognized in EMA top 3 for artificial intelligence and machine learning for optimizing DevOps, IT operations and business.”
-EMA Top 3 Report and Decision Guide for Enterprise, Q4 2018