One platform to collect, govern and analyse your data
IBM Software Hub, formerly IBM Cloud Pak for Data, brings data management, governance, integration and data science together on one platform, so your teams stop stitching separate tools and get to results sooner. We design it, implement it and build your data products on it.
What you get with IBM Software Hub
Data where it is
Make data accessible securely at its source through data virtualization, without migrating everything into one store first.
Governance built in
Policies, security and compliance are part of the platform, so a user who finds a data set also knows whether and how it may be used.
Models that reach production
Build, deploy and manage machine-learning models through one lifecycle, in a shared environment for data scientists, developers and analysts.
Runs where you need it
The platform runs on Red Hat OpenShift, on premises and on private or public clouds, and its services are added as you need them.
What we do for you
- Assessment. We look at your data landscape and decide with you where a platform helps and where it does not.
- Platform build. Installation on Red Hat OpenShift, sizing, security and integration with your sources.
- Data catalogue and governance with IBM watsonx.data intelligence (formerly IBM Knowledge Catalog): automated discovery, a business glossary, policies, quality and lineage.
- Data pipelines. Integration and replication flows that deliver data to your reports and models.
- Data science environment. Tools, processes and governance for building and running models.
Ready-made for banks
Analytics-in-a-Box for Banking is our data and analytics solution built on IBM Software Hub (formerly Cloud Pak for Data). It adds a banking industry data model and modules for customer insights, financial reporting and regulatory reporting. Read more under Data & AI.
News, cases and resources on IBM Software Hub (formerly Cloud Pak for Data)
A Comprehensive Guide for the Modern Data Catalog
An e-book on what a modern data catalog does, how to establish a business taxonomy, and five use cases for overcoming data challenges.
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Read more →Harness your data, build intelligent apps
Simplify and automate how your organization turns data into insights within a unified — all in one — design.
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