What is the primary assumption behind the ICES model when evaluating effectiveness?

The ICES model, which stands for Integrity, Currency, Ease of retrieval, and Security, places paramount importance on the integrity of data when evaluating effectiveness. Integrity of data refers to the accuracy and reliability of information. In the context of data analytics, ensuring that the data is trustworthy is essential for making informed decisions. If the underlying data lacks integrity, any analysis derived from it could lead to erroneous conclusions and might adversely affect outcomes.

When assessing the effectiveness of any data system or model using the ICES framework, it is crucial to verify that the data is not only correct but also maintained consistently over time. This foundational assumption supports all other aspects of data management; without reliable data, considerations like security, currency, and ease of retrieval become less valuable since the quality of insights generated from compromised data is fundamentally flawed. Therefore, emphasizing the integrity of data is at the core of the ICES model.