Social media users and followers in a graph database is an example of semi-structured data.
Explanation:
Structured data refers to highly organized information that can be easily stored in tables and rows (like in relational databases).
Unstructured data refers to information that doesn't have a predefined data model or is not organized in a predefined manner (like text documents, videos).
Semi-structured data lies between the two, having some organizational properties but not enough to fit into a strict relational database. Graph databases, which store data in nodes, edges, and properties, are a typical example of semi-structured data because they can handle a variety of data types and relationships without a rigid schema.
Therefore, the correct answer is semi-structured data.
Semi-structured data is data that does not conform to a strict relational model but still has some organizational structure, often through key-value pairs or graph nodes and edges. In a graph database, relationships between social media users and their followers are represented as edges connecting different nodes (users), providing a form of structure but not as rigid as in traditional relational databases.
Answer: Semi-structured
The correct answer is A - "Semi-structured data". Social media users and followers in a graph database are example of semi-structured data. Semi-structured data has some structure, but not enough to fit into a traditional database. It often includes unstructured elements, such as text and images. Semi-structured data is useful for graph databases, which can help to uncover patterns and relationships in the data.
https://learn.microsoft.com/en-us/azure/architecture/data-guide/big-data/non-relational-data
Graph as non relational db.
https://learn.microsoft.com/en-us/azure/architecture/guide/technology-choices/data-store-overview
Nodes are similar to table rows or JSON documents.
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I bet semi-structured, even if microsoft do not directly put it in a specific area (as per document or search service).
semi-structured data:
A graph database is a type of NoSQL database that stores data as nodes and edges, which represent entities and relationships². A graph database does not have a rigid schema or structure, but it has some organizational properties that make it easier to analyze, such as metadata or labels attached to nodes and edges². Therefore, a graph database falls into the category of semi-structured data, which is data that has some consistent and definite characteristics, but does not conform to a predefined data model¹. An example of semi-structured data in a graph database is social media users and followers, where each user is a node with attributes such as name, age, location, etc., and each follower relationship is an edge with a direction and a weight.
Type this in ChatGPT "Social media users and followers in a graph database would be an example of structured, semi-structured or unstructured data?" and you'll get a great description and answer of "Structured data".
As per the second video in this link -
https://learn.microsoft.com/en-us/training/modules/choose-storage-approach-in-azure/2-classify-data
It is semi-structured.
Social media users and followers data has a clear structure of followers and users but it can have different properties and different values for each user, that's why it can be considered as semi-structured data.
Structured.
Social media users and followers in a graph database is an example of structured data.
Structured data is data that is organized and can be easily stored, queried, and analyzed in a specific format. Graph databases are designed to store and manage data in a structured way. They are optimized for handling data that is organized in a graph-like structure, which includes nodes (representing entities, such as social media users), and edges (representing relationships between those entities, such as followers).
Unstructured data is data that does not have a specific format and can't be easily stored, queried, and analyzed. Examples of unstructured data include text, images, videos, and audio files.
Semi-structured data is data that has some structure but not as defined as structured data. Examples of semi-structured data include JSON or XML files, which have a defined structure but allow for nested elements and variations in structure.
I tend to believe it is structured, google search showing below :
Both structured and unstructured types of data are created from social media use. The text in a social media post is unstructured data, while information about friendships, followers, groups or networks is structured.
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