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[24] [page needed] Big data philosophy encompasses unstructured, semi-structured and structured data; however, the main focus is on unstructured data. [25] Big data "size" is a constantly moving target; as of 2012 ranging from a few dozen terabytes to many zettabytes of data. [26]
Semi-structured data [1] is a form of structured data that does not obey the tabular structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data.
Unstructured data (or unstructured information) is information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured information is typically text -heavy, but may contain data such as dates, numbers, and facts as well.
A data lake can include structured data from relational databases (rows and columns), semi-structured data (CSV, logs, XML, JSON), unstructured data (emails, documents, PDFs), and binary data (images, audio, video). [3] A data lake can be established on premises (within an organization's data centers) or in the cloud (using cloud services).
Data models are often complemented by function models, especially in the context of enterprise models. A data model explicitly determines the structure of data; conversely, structured data is data organized according to an explicit data model or data structure. Structured data is in contrast to unstructured data and semi-structured data.
Structure mining or structured data mining is the process of finding and extracting useful information from semi-structured data sets. Graph mining, sequential pattern mining and molecule mining are special cases of structured data mining [ citation needed ] .
Data Vault 2.0 [20] [21] has arrived on the scene as of 2013 and brings to the table Big Data, NoSQL, unstructured, semi-structured seamless integration, along with methodology, architecture, and implementation best practices.
Data Lake Storage is a cloud service to store structured, semi-structured or unstructured data produced from applications including social networks, relational data, sensors, videos, web apps, mobile or desktop devices.