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CP4D v4.x Watson Knowledge Catalog

Course Overview / Prerequisites / Audience / Topics

Course Overview

This course teaches how to use IBM Watson Knowledge Catalog on Cloud Pak for Data for managing and governing data catalog. Students will gain experience by creating Governance artifacts and adding data assets to a governed catalog so that data protection rules are automatically enforced to protect sensitive data from unauthorized access. This course also covers the data curation process by performing automated data discovery to quickly analyze the source data quality, understand automated term assignments and review the quality score for data assets. They will also learn how to quickly find and access data, self-service data preparation (data refinery), data request and Watson APIs to consume the business-ready data from the Watson Knowledge Catalog.

Prerequisites

• Familiarity with relational database concept is desirable but not required.

Audience

  • Business Users
  • Business Analysts
  • Data Stewards
  • Governance users
  • Data Quality Analysts
  • Data Scientist
  • Catalog Administrators / Metadata Administrators
  • Data Engineers
  • Developers

Topics

Day1:

  • Introduction to Information Analyzer and Information Analyzer roles
  • Information Analyzer thin client
  • Setting up the Data Connection
  • Import metadata using IMAM for database tables and flat files
  • Creating import area
  • Create and configure IA Project
  • Adding users to the IA project and assign roles
  • Overview of column analysis, review & perform below tasks with an example using thin client
  • Run Column analysis
  • Create Data classification and review its types
  • Domain and completeness
  • Format
  • Capture notes
  • Overview of virtual column and perform below tasks with an example using thin client
  • Creating virtual column
  • Analyze virtual column
  • Create virtual table using IA thin client
  • Create reference table
  • Overview of below analysis & perform analysis with an example
  • Table Analysis
  • Primary Key Analysis
  • Multi column Key Analysis
  • Cross Table Analysis
  • Baseline Analysis

Day2:  

  • Identify redundant data between tables
  • Create different types of Reports
  • Run different reports
  • View reports being generated
  • Publish analysis results and view it with an example in DataStage
  • Export reference table with an example
  • Overview of Data rule and Data rule definition
  • Creating a Data rule and Data rule definition
  • Overview of Rule set
  • Binding Data rules to Rule set
  • Create a Data Rule set with an example
  • Write the output of Data Rule & Rule set to tables
  • Setting output system table under rule bindings
  • Create benchmarks for Data rule
  • Purging output table with below methods
  • Automatic
  • Global
  • Rule
  • Manual
  • Overview of Metrics
  • Creating Metrics
  • Running Metrics and scheduling it
  • Export DDL from table in IA to a file

Day3:

  • Purging output tables in IA with an example
  • Setting auto purge properties
  • Automatic term assignment in IA using thin client with an example
  • Overview of Data Quality Dimensions with few examples
  • Overview of Automation rules
  • Configuring and creating Automation rules
  • Running and viewing Automation rules status
  • Migrate Data rules with binding from lower environment to higher environment
  • Example of a Data class linking with data rule to all related database assets
  • Best practice to Run 100’s of Data Rules in a daily production schedule from a scheduler
  • Evaluating Performance while running large number of rules
  • Prepare and rundelta data on daily basis for Data rules execution

Day4:

  • Archiving strategy for the exceptions created on daily basis from Data Quality rules and tables created from analysis
  • Migrate IA assets from lower environment to higher environment with an example
  • Auto bindings for Data elements to Data rules
  • Overview of Information Server Enterprise Search its usage and administration
  • Overview of Data Quality Exception Console
  • Review an IA Data rule exception data in Data Quality Exception console for the records that do not meet a Data rule condition
  • New features in IA 11.7.1.1
  • Q&A
Start Date: 08/14/2023
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Duration: 5 Days(5 hours a day)

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Time: 8 AM EET

Delivery Method: Virtual

Language: English

Course ID: NFCP4D-WKC-EET17

Price: $2500

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