In CPMAI Step 2: Data Knowledge, what is assessed regarding the data?

The assessment of data in Step 2 of the CPMAI framework focuses on its availability, accessibility, and quality. This step is critical because understanding the characteristics of the data is foundational for any AI or data-driven project.

Availability refers to how accessible the data is for use – whether it can be easily obtained and utilized by the team working on the AI initiative. Accessibility assesses whether the required stakeholders can retrieve and work with the data efficiently. Quality pertains to the accuracy, reliability, and trustworthiness of the data, which greatly influences the outcomes of any analytics or AI model built from it. High-quality data is essential for producing valid and actionable insights, making this step a vital part of the overall data handling and analysis process in AI projects.

While factors like size, profitability, and security are important in their own right, they do not encompass the core aspects needed to make informed decisions regarding which data to utilize and how to prepare it for analysis and model training.