ETL Data Quality Testing Best Practices

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Why do my ETL data quality testing techniques fail to identify bad data?

Bad data costs organizations dearly in correction activities, lost customers, missed opportunities, and incorrect decisions.

How to perform ETL Data Quality Testing to find bad data?

Impact of poor data

Poor data can lead to bad business decisions

Delays in delivering data to decision makers

Lost customers through poor service

ETL Testing Techniques

Number of Records Validation

Data Completeness

Not Null Validation

Validate valid values

Frequency Distribution

Min and Max Validations

Duplicate Records

Pattern Check

Consistency

Precision

Timeliness

Business Rules

Data Type Check

Size & Length Validation

A firm’s basis for competition . . . has changed from tangible products to intangible information. A firm’s information represents the firm’s collective knowledge used to produce and deliver products and services to consumers. Quality information is increasingly recognized as the most valuable asset of the firm. Firms are grappling with how to capitalize on information and knowledge. Companies are striving, more often sliently, to remedy business impacts rooted in poor quality information and knowledge.

– Kuan-Tsae Huang, Yang W. Lee and Richard Y. Wang