Kurs informasjon: IBM InfoSphere Information Analysis V8.7 - SPVC

This is the Self-paced Virtual version of Classroom course IBM InfoSphere Information Analysis V8.7 (KM801NO), Instructor-led Online course IBM InfoSphere Information Analysis V8.7 (ILO) (3M801NO) and Web-based course IBM InfoSphere Information Analysis V8.7 - Web (1M801NO).

This is a self-paced online course. The average amount of time to complete this course is 32 hours. Once you receive your access information, you will have 60 days to complete this course. Please do not make travel arrangements for this course. After you receive confirmation that you are enrolled, you will be sent further instructions to access the course.

This course introduces the concepts and methods used to perform information analysis. IBM InfoSphere Information Analyzer, Business Glossary, and QualityStage will be used to perform data profiling,data assessment and meta data enrichment tasks.

Students will learn how to use the IBM InfoSphere suite to analyze data and report results to business users. This course will also explore techniques for delivering data analysis results to ETL developers and show how to develop more meaningful meta data to reflect data discovery results. An information analysis methodology and a case study will be used to guide hands-on labs.

The self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day. Once you have accessed the course, instructor help is available via the course forum Monday through Friday; questions will be responded to within 24 hours.

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This is a basic course for business data analysts who want to profile and assess data using Information Analyzer.

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Students should have:

• Knowledge in UNIX or Windows NT administration
• Data modeling experience (helpful)
• Familiarity with Open Database Connectivity (ODBC) and relational database access techniques

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• Analyze data structures to determine agreement with documented metadata
• Discover data anomalies
• Identify invalid and incomplete data
• Determine primary keys to table structures
• Add business meaning to data
• Produce deliverables that can be used by business users and ETL developers
• Configure Information Analyzer
• Administer the Information Analyzer environment
• Understand security considerations around data analysis
• Understand the methodology supporting data analysis
• Use Information Analyzer to analyze data content and structure

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• Information Analysis concepts
• Information Server overview
• Information Analyzer overview
• Information Analyzer Setup
• Column analysis
  • Concepts
  • Basic data profiling techniques in practice
• Primary key analysis
  • Concepts
  • Basic data profiling techniques in practice
• Foreign key and cross domain analysis
  • Concepts
  • Basic data profiling techniques in practice
• Baseline analysis
• Reporting and publishing
• Extending the meta data using Business Glossary and Information Analyzer
• Information Analyzer Data Rules and Metrics
• Data quality assessment using QualityStage

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