Information & Analysis Quality

Information & Analysis Quality

IHS has defined the data transformation process into logical steps, each designed to reduce the uncertainty that comes with using raw data.

The IHS steps for data transformation are: Source, Capture, Match, Identify, Relate, Analyze, Model and Forecast.

Maintaining the order of the steps and performing quality assessments at each are important because each step is dependent on the preceding steps. At IHS, quality at each step is assessed against four dimensions:

Correctness: Validating data accuracy relative to external reference points

Currency: Delivering new and updated content in a timely manner

Completeness: Providing the right data attributes and analysis

Consistency: Ensuring standardized identities, definitions and content across databases and products

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