- Date of last update: 10/02/2019
IBM® Cloud Pak for Data
Your enterprise has data. Lots of data. You need to use your data to generate meaningful insights.
But your data is useless if you can't trust it or access it. Cloud Pak for Data lets you do both by enabling you to connect to your data (no matter where it lives), govern it, and find it, so that you can put your data to work quickly and efficiently.
Learn more in the https://www.ibm.com/analytics/cloud-pak-for-data
Single, unified platform
Reduce your time to value with a single platform that combines data governance and analytics designed for data stewards, data engineers, data scientists, and business analysts.
Create data sets from disparate data sources so that you can query and use the data as if it came from a single source.
Know your data inside and out. Ensure that your data is high quality, aligns with business objectives, and complies with regulations.
Built in analytics and AI
Unearth the meaning in your data, whether you prefer to work in JupyterPython Notebooks or quickly create visualizations from the analytics dashboards.
Minimum scheduling capacity:
|Software||Memory (GB)||CPU (cores)||Disk (GB)||Nodes|
|Cloud Pak for Data||64||16||100||3|
If desired, you can set the consoleRoutePrefix parameter. This value is used as the subdomain in the URL for the Cloud Pak for Data landing page.
You need to set a password for the admin username. After the installation completes, login on the Cloud Pak for Data dashboard with the username "admin" and the password you have defined.
The installation process will not make any verification for available resources (memory, cpu) on the cluster. Make sure have enough resources available to deploy Cloud Pak for Data if you are running other applications on your cluster.
Cloud Pak for Data is configured to use dynamic provisioning. The installation will require about 700GB of your storage. Make sure to select a storageclass with enough resource available.
Documentation for Cloud Pak for Data can be found at Cloud Pak for Data documentation.
You can also learn more by viewing docs.