IBM InfoSphere Information Analyzer Essentials v11.5

In this course, 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 demonstrate 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 exercises.

Objetivos

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

Administración y programación bases de datos

Disponible en formato e-learning

Disponible en formato presencial

Disponible en formato a distancia

Subvención disponible
A través de Fundae, cumpliendo requisitos.

Duración
20 horas

  • Dificultad 50% 50%
  • Nivel alcanzado 80% 80%

Dirigido a

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.

Conocimientos requeridos

You should have:

Data modeling experience helpful
Familiarity with Open Database Connectivity (ODBC) and relational database access techniques

Temario

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 Information Governance Catalog and Information Analyzer
Data Rules and Metrics

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