That entails analysis of unstructured image data to create structured fields that can be joined to existing data for analysis and, ultimately, to drive editorial decision-making. In this article ...

In the dynamic world of data science, the conversion of unstructured data into structured data is a key process. This transformation is crucial for enabling more efficient data analysis and ...

Unstructured data refers to information that does not have a predefined data model or organized format, making it more challenging to store, process, and analyze compared to structured data.

Unstructured data — information that doesn’t follow conventional models or fit into structured database formats — represents more than 80% of all new enterprise data. To prepare for this ...

Structured data is the most critical data type to maximize AI's benefits. Data is structured or unstructured depending on the format and schema it is based upon. A schema describes the ...

This type of data is typically numeric or categorical and adheres to a strict schema, making it predictable and easier to manage compared to unstructured or semi-structured data. Commonly used in ...

From litigation documents to case files, contracts, and discovery materials, legal institutions are witnessing explosive data ...

Analysis of unstructured image data can create structured fields that can drive editorial decision-making. Elsewhere, backups – long consigned to dusty and hard-to-access tape archives – are ...

However, ensuring this data quality across both structured and unstructured data sets is no simple task, particularly in organizations that have not invested in the right people and tools.

For instance, knowing that a specific client's data was breached provides the opportunity to proactively address the issue. Although risks exist for both structured and unstructured data ...