Kursbeskrivning: IBM InfoSphere Information Analysis 9.1

You will learn how to use the IBM InfoSphere suite to analyze data and report results to business users. Information discovered during analysis will be used to construct data rules. 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.

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.

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Roadmaps:

• Information Analysis – Business Analyst/Data Steward
• Information Analysis – Data Quality Architect

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This basic course is for business data analysts who want to profile and assess data using Information Analyzer, also data quality analysts who need to measure data quality.

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You should have:

• Familiarity with Open Database Connectivity (ODBC) and relational database access techniques

Data modeling experience is helpful.

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• Analyze data structures to determine agreement with documented metadata
• Discover data anomalies
• Identify invalid and incomplete data values
• Determine potential 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
• Use Information Analyzer to construct data rules and utilize IBM-supplied data rule templates

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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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