Overview

This learning offering will tell a holistic story of Cloud Pak for Data including collaboration across an organization, which is key in this platform. Applicable to all personas. Multiple use cases will provide understanding of how organizations can benefit from Cloud Pak for Data. A variety of features will also be explored, providing students with the insight on how to use the platform. This learning is relevant for Cloud Pak for Data and Cloud Pak for Data System.

Audience

Data Engineer, Data Steward, Data Scientist, Business Analyst, Application Developer, Administrator

Prerequisites

IBM Demo assets: IBM Cloud Pak for Data (https://www.ibm.com/demos/collection/IBM-Cloud-Pak-for-Data/)

Objective

• Introduction to IBM Cloud Pak for Data • Red Hat OpenShift Container Platform: overview • Collaboration and workflows • Collect data • Organize data • Prepare data • Analyze data • Services and integrations • Administer the platform • Assessment

Course Outline

Introduction to IBM Cloud Pak for Data • Describe IBM Cloud Pak for Data • Identify how IBM Cloud Pak for Data makes you ready for artificial intelligence (AI) • Describe, at a high level, the IBM Cloud Pak for Data architecture • Describe how to collaborate within IBM Cloud Pak for Data • Describe the typical end-to-end data and analytics workflow in IBM Cloud Pak for Data • Identify what you will be doing in this training Red Hat OpenShift Container Platform: overview • Describe how the Red Hat OpenShift Container Platform relates to IBM Cloud Pak for Data • Describe the role of containers, Kubernetes, and Helm • Describe how Red Hat OpenShift is a layered system • Describe, at a high level, the Red Hat OpenShift architecture • Describe, at a high level, how Red Hat OpenShift is secured Collaboration and workflows • Identify the default roles in IBM Cloud Pak for Data • Describe how permissions work in IBM Cloud Pak for Data • Describe a typical workflow • Create a project • Search for data • Request data Collect data • Identify how you connect to data sources in IBM Cloud Pak for Data • Identify ways in which you can add data to a project • Identify supported data sources • Describe how to work with an integrated database • Create a connection to a data source Organize data • Describe the Watson Knowledge Catalog service and what you can do with it • Describe how you can work with catalogs • Describe how you can govern and curate data using Watson Knowledge Catalog • Identify how governance artifacts and governance tools work together • Identify how you can govern data to comply with regulations • Perform automated discovery and work with the default catalog Prepare data • Identify ways in which you can prepare data for use in projects • Describe how to transform data using the DataStage service • Refine data using the Data Refinery service • Virtualize data using the Data Virtualization service Analyze data • Identify how you can analyze data in IBM Cloud Pak for Data • Analyze data using notebooks • Identify other tools that you can use to analyze data • Automatically analyze your data using the AutoAI tool • Deploy machine learning (ML) models Services and integrations • Identify how you can extend the functionality of IBM Cloud Pak for Data • Identify the services that are available in the catalog • Identify the services that are available outside of the catalog • Describe how you can address common business issues by using industry accelerators • Describe how you can integrate IBM Cloud Pak for Data with other applications Administer the platform • Identify how you can administer the cluster for IBM Cloud Pak for Data • Identify how you can administer the web client for IBM Cloud Pak for Data Assessment