Chapter 3. Validating Data

This chapter contains recipes that show some of the techniques for validating data and handling invalid rows.

  • Enabling and disabling reject flows
  • Gathering all rejects prior to killing a job
  • Validating against the schema
  • Rejecting rows using tMap
  • Checking a column against a list of allowed values
  • Checking a column against a lookup
  • Creating validation rules for more complex requirements
  • Creating binary error codes to store multiple test results

Introduction

Clean, timely, and correct data is a business-critical resource for most organizations, because it enables (but is not restricted to) more accurate decision making, compliance, and improved efficiency.

Data integration is often the first point of contact for data arriving into ...

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