IBM Knowledge Catalog on IBM Cloud Pak for Data 4.8: Advanced Data Governance (6XL942G)

Overview

This course offers solution architects more experience with IBM Knowledge Catalog for IBM Cloud Pak for Data. You learn to tune and customize governance workflows and artifacts to enhance data protection, quality, and findability. You gain skills in enriching metadata, building data quality rules, customizing asset properties, and governing virtual data.

Audience

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

Prerequisites

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

  • Summarize the foundational concepts of IBM Knowledge Catalog 
  • Define a governance workflow
  • Create a governance framework that protects data
  • Describe data by importing a business glossary
  • Evaluate the contents of a data set
  • Use governed data assets in projects

 

You can review these skills in the IBM Knowledge Catalog on IBM Cloud Pak for Data 4.8: Enterprise Catalog Management and Data Governance course.

Objective

By the end of this course, you will be able to:

  • Construct workflow configurations for governance artifacts
  • Create custom roles, properties, relationships, and asset types to capture important details about data
  • Build a complete and meaningful business glossary to establish a trusted governance foundation
  • Apply metadata and regular expressions to remediate the quality of data
  • Augment cataloged data to enhance trust and use
  • Govern virtualized data
  • Examine data asset relationships
részletek megjelenítése

Course Outline

  • Introduction
  • Manage users and collaboration
  • Define data governance workflows 
  • Define the business vocabulary
  • Curate and enrich data assets
  • Manage data quality
  • Augment cataloged data
  • Govern virtualized data
  • Analyze the data
  • Review and evaluation