IBM Watson Knowledge Catalog Methodology - eLearning
- Codice corso: W7071G-WBT
- Durata corso: 4hr
Overview
This training offering provides business analysts with an introduction to the basics of IBM Watson Knowledge Catalog. They will learn how to access the Watson Knowledge Catalog and gain skills in creating catalogs, populating them with assets, and then managing the assets in the catalog.
Audience
Business Analysts
Prerequisites
- Knowledge of your business requirements
Objective
• Introduction to IBM Watson Knowledge Catalog
• Work with assets
• Refine data
• Assessment quiz
Course Outline
Introduction to IBM Watson Knowledge Catalog
• What is IBM Watson Knowledge Catalog?
• How IBM Watson Knowledge Catalog addresses the challenge of data and AI
• What is a catalog?
• What is a project?
Work with assets
• What is an asset?
• Work with assets in a catalog
• Add files, connections, and connected assets in projects and catalogs
• Add an asset from a catalog to a project
• Publish assets from a project into a catalog
• Discover data assets from a connection in a catalog or project
Refine data
• Describe using Data Refinery to refine data
• Add data to Data Refinery and specify the format
• Validate your data
• Visualize your data
• Manage Data Refinery flows
• Copy data from a source to a target
Assessment quiz
Course Outline
WebSphere product family overview
WebSphere Application Server architecture - stand-alone
Exercise: Profile creation
WebSphere Application Server administrative console
Exercise: Exploring the administrative console
Introduction to the PlantsByWebSphere application
Application assembly
Exercise: Assembling an application
Application installation
Exercise: Installing an application
Problem determination
Exercise: Problem determination
Introduction to wsadmin and scripting
Exercise: Using wsadmin
WebSphere security
Exercise: Configuring WebSphere Application Server security
Exercise: Configuring application security
Performance monitoring
Exercise: Using the performance monitoring tools
Course summary