MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Common examples of applications that rely on structured data include customer relationship management (CRM), invoicing systems, product databases, and contact lists. Unstructured data includes various content such as documents, videos, audio files, posts on social media, and emails.

Detailed explanation-2: -While in unstructured data, textual queries are possible, the performance is lower than semi-structured and structured data. Structured data is quantitative, i.e., it consists of hard numbers or things that can be counted. It is qualitative, as it cannot be processed and analyzed using conventional tools.

Detailed explanation-3: -Any clearly labeled database of information (such as an Excel file, SQL database, or data warehouse) can be considered structured data. This type of data is stored in tables, with clear relationships between the different rows and columns.

Detailed explanation-4: -Structured data represents data in a flat table. In contrast, semi-structured data can contain hierarchies of nested information. This nested data structure makes semi-structured data ideal for the variety of data coming from apps, devices, and channels.