What is cloud Pak for data as a service?
The Red Hat Ecosystem Catalog is the official source for discovering and learning more about the Red Hat Ecosystem of both Red Hat and certified third-party products and services. Show
We’re the world’s leading provider of enterprise open source solutions—including Linux, cloud, container, and Kubernetes. We deliver hardened solutions that make it easier for enterprises to work across platforms and environments, from the core datacenter to the network edge. Before we get started with the workshop, you will need to download some assets and setup your environment. This section is broken up into the following steps:
Download Assets¶Various parts of this workshop will require the attendee to upload files or run scripts. These artifacts have been collected in the following two zip files which you can download using the links below. For each line below, click on the
Create IBM Cloud Account and Services¶We need to provision our Cloud Pak for Data as a Service instance. Cloud Pak for Data provides you with an integrated set of capabilities for collecting and organizing your data into a trusted, unified view, and then creating and scaling AI models across your business. Create Cloud Pak for Data Services¶
Verify Service Instances¶
Create a Project and Deployment Space¶Import the Project¶In Cloud Pak for Data, we use the concept of a project to collect / organize the resources used to achieve a particular goal (resources to build a solution to a problem). Your project resources can include data, collaborators, and analytic assets like notebooks and models, etc.
Associate a Watson Machine Learning Service instance to the project¶You will need to associate a Watson Machine Learning service instance to your project in order to run Machine Learning experiments.
Create a Deployment Space¶Cloud Pak for Data uses the concept of
Get API Access Details¶In some parts of this workshop, you will be using the Watson Machine Learning (WML) SDK / APIs to perform operations on your Watson Machine Learning instance. To programmatically access your Watson Machine Learning instance, you will need to provide the API key for your IBM Cloud account as well as the location of the WML service instance. Get an API Key¶You will use the IBM Cloud Console to generate the IBM Cloud API key.
Get the WML Service Instance Location¶You will need to know the location (i.e region code) where your machine learning service instance is provisioned. If you know the region where you provisioned the service, you can determine the region code from the table below: RegionRegion CodesDallasus-southTokyojp-tokLondoneu-gbFrankfurteu-deIf you are not sure of the region you provisioned, you can use the IBM Cloud CLI to obtain the location of the machine learning service instance.
Conclusion¶We have now completed creating an IBM Cloud account, a Cloud Pak for Data as a Service instance, and the project and deployment space that we will use in the rest of this workshop. We have also obtained the IBM Cloud API key that we will use to invoke APIs for your services. What is IBM Cloud Pak for data as a service?IBM Cloud Pak for Data as a Service brings together integrated data and AI services, fully managed on the IBM Cloud. Speed time to innovation by uniting the historically siloed tools, processes and talent required for enterprise data management, governance and analysis within a collaborative self-service environment.
What is the main use cases for cloud Pak for data?You can use IBM Cloud Pak for Data with different services to implement use cases that help you build a trusted data foundation for your AI operations.. Financial planning and analysis.. Workforce planning.. Sales forecasting.. Supply chain planning.. What is cloud Pak system?This system of hardware and software with integrated VMware and Red Hat helps you build, deploy and manage containerized apps and Kubernetes workloads on premises, at the edge or on any cloud.
What is included in IBM cloud Pak?IBM Cloud Pak for Data use cases. AI governance.. Data observability.. Data governance and privacy.. Multicloud data integration.. Customer 360.. |