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. A generic use case 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 WBT contains instructional and interactive content, demonstrations and hands-on exercises (on Cloud Pak for Data on IBM Cloud).

Audience

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

Prerequisites

IBM Demo assets: IBM Cloud Pak for Data, in particular Overview Cloud Pak for Data (https://www.ibm.com/demos/collection/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  • Infuse data • 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  • Administer the platform • Describe a typical workflow • Create an analytics 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 virtualize data using the Data Virtualization service • Describe how you can refine data using the Data Refinery service • Identify how you can access trusted master data with IBM Master Data Connect • Describe how you can build trust in unstructured data with IBM Watson Knowledge Catalog Instascan • Identify how you can manage test data using Virtual Data Pipeline (VDP) Analyze data  • Identify how you can analyze data in IBM Cloud Pak for Data  • Automate building machine learning models with AutoAI experiment  • Deploy machine learning models • Analyze data using notebooks • Identify other tools that you can use to analyze data Infuse data • Identify how you can perform self-service analytics with Cognos Analytics • Describe how you can extract answers from complex business documents with Watson Discovery • Identify how you can deliver engaging, unified problem-solving experiences with Watson Assistant • Describe you can accurately transcribe the human voice with Watson Speech to Text • Identify how you can convert written text to natural-sounding speech with Watson Text to Speech • Describe how you can automate planning, budgeting, and forecasting with Planning Analytics Assessment