Your business has a lot of data. You need to use your data to generate meaningful insights that will help you avoid problems and achieve your goals. But your data is useless if you can't trust or access it. Collect, organize and analyze your data and generate meaningful insight with an extensible end-to-end management, analytics and artificial intelligence platform. Accelerate your journey to AI to transform how your business operates with an open, extensible platform that runs on any cloud.
The IBM Cloud Pak® for Data platform helps increase productivity and reduce complexity, providing a modern data and analytics architecture that is elastic, scalable and reliable. The platform lowers total cost of ownership, accelerates innovation based on open source technologies, and fully supports multi-cloud environments.
IBM Cloud Pak® for Data offers innovative technologies such as:
- IBM Watson® AI technology, IBM Watson Knowledge Catalog und IBM Hybrid Data Management.
- Red Hat® OpenShift® with a growing range of microservices in any cloud, such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud, IBM Cloud™ or private clouds.
- Core services that include IBM Master Data Connect and IBM Watson Knowledge Catalog InstaScan.
- Advanced services such as IBM Master Data Management, IBM Db2®, IBM Watson Studio and a growing ecosystem of data and AI services.
IBM Cloud Pak® for Data provides a data fabric architecture, an architectural pattern for managing highly distributed and disparate data. It is designed for hybrid and multi-cloud data environments. With intelligent knowledge catalog capabilities, you can elevate data into enterprise assets that are managed globally, regardless of where the data is stored, processed, or used. Thanks to this architecture, you can:
- Simplify and automate data access across multi-cloud and on-premises data sources without having to move data.
- Universally secure the use of all data regardless of source.
- Provide business users with a self-service environment for searching and using data.
- Leverage AI capabilities to automate and orchestrate the data lifecycle.