Students 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.

If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.

http://www.ibm.com/training/terms

• 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

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

You must have familiarity with:

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

Data modeling experience is helpful.

• 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