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IBM Knowledge Catalog on IBM Cloud Pak for Data 4.8: Enterprise Catalog Management and Data Governance

This course provides Solution Architects an introduction to the basics of IBM Knowledge Catalog for IBM Cloud Pak for Data. You learn to access IBM Knowledge Catalog through the service, and gain...

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$1,055 USD
Course Code 6XL934G
Duration 7 hours
Available Formats Classroom

This course provides Solution Architects an introduction to the basics of IBM Knowledge Catalog for IBM Cloud Pak for Data. You learn to access IBM Knowledge Catalog through the service, and gain skills in creating catalogs, populating them with assets, and then managing the assets in the catalog through a governance framework.

Skills Gained

After completing this course, you should be able to:

  • Summarize the foundational concepts of IBM Knowledge Catalog
  • Create a governance framework that protects data
  • Describe data by adding classifications and business terms
  • Curate the data by metadata enrichment and quality assessment
  • Evaluate the contents of a data set
  • Use governed data assets in projects
  • Establish reporting to query metadata from IBM Knowledge Catalog

Who Can Benefit

This course is designed for solution architects, but it is also relevant for other enterprise roles that want to understand and apply data governance, quality, workflow, and catalog concepts in IBM Knowledge Catalog.

Prerequisites

Before taking this course, you should be able to complete the following tasks: 

  • Explain the purpose of Cloud Pak for Data and the value it brings to the business
  • Describe the architecture of Cloud Pak for Data
  • Summarize the ModelOps process
  • Differentiate between Cloud Pak for Data and Red Hat OpenShift Container Platform
  • Define the AI Ladder and its associated roles and services
  • Log in to Cloud Pak for Data and complete an analytics project

Course Details

Course Outline

  • Introduction to enterprise catalog management with IBM Cloud Pak for Data
  • Prepare the IBM Knowledge Catalog environment
  • Define and implement a governance framework
  • Describe the data
  • Curate the data
  • Apply data quality rules
  • Analyze the data
  • Configure reporting on data
  • Review and evaluation