Informatica IDQ

Index:

• Introduction to Informatica Data Quality:

• Overview of Informatica Data Quality architecture, components, features, and benefits. Understanding the role of data quality in enterprise data management.

• Installation and Configuration:

• Installing and configuring Informatica Data Quality environment. Setting up Informatica services, repositories, and connectivity to data sources for data profiling and cleansing.

• Data Profiling and Analysis:

• Performing data profiling and analysis using Informatica IDQ. Discovering data quality issues, anomalies, and inconsistencies in source data.

• Data Standardization and Cleansing:

• Implementing data standardization rules and data cleansing transformations in Informatica IDQ. Developing cleansing mappings and workflows to improve data accuracy and consistency.

• Matching and Deduplication:

• Configuring and executing data matching and deduplication processes in Informatica IDQ. Identifying and eliminating duplicate records across datasets.

• Data Quality Rules and Scorecards:

• Defining and managing data quality rules, scorecards, and metrics in Informatica IDQ. Monitoring data quality trends and performance over time.

• Integration and Workflow Development:

• Designing and developing data quality workflows and integrations in Informatica IDQ. Creating reusable mappings, transformations, and workflows for data quality tasks.

• Monitoring and Reporting:

• Monitoring Informatica IDQ jobs and data quality processes using built-in monitoring tools and dashboards. Generating reports and metrics to measure data quality improvements.

• Security and Access Control:

Implementing security measures in Informatica IDQ environments. Managing user access, roles, privileges, and securing sensitive data during data quality operations