Table of Contents

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  1. Preface
  2. Introduction to Informatica Big Data Management
  3. Mappings
  4. Sources
  5. Targets
  6. Transformations
  7. Cluster Workflows
  8. Profiles
  9. Monitoring
  10. Hierarchical Data Processing
  11. Hierarchical Data Processing Configuration
  12. Hierarchical Data Processing with Schema Changes
  13. Intelligent Structure Models
  14. Stateful Computing
  15. Connections
  16. Data Type Reference
  17. Function Reference

User Guide

User Guide

Step 2. Cleanse the Data

Step 2. Cleanse the Data

Cleanse the data by profiling, cleaning, and matching your data. You can view data lineage for the data.
You can perform data profiling to view missing values and descriptive statistics to identify outliers and anomalies in your data. You can view value and pattern frequencies to isolate inconsistencies or unexpected patterns in your data. You can drill down on the inconsistent data to view results across the entire data set.
You can automate the discovery of data domains and relationships between them. You can discover sensitive data such as social security numbers and credit card numbers so that you can mask the data for compliance.
After you are satisfied with the quality of your data, you can also create a business glossary from your data. You can use the Analyst tool or Developer tool to perform data profiling tasks. Use the Analyst tool to perform data discovery tasks. Use Metadata Manager to perform data lineage tasks.

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