Hey Dataeum fans! 👋😊
Data is a thorny subject. Can we group all of its variations into distinct types, categories and classifications? We’ll try:
1 - Big data
That amount of data that will not practically fit into a standard database for analysis and processing caused by the huge volumes of information being created by human and machine-generated processes.
2 - Structured, unstructured, semi-structured data
All data has structure of some sort. Delineating between structured and unstructured data comes down to whether the data has a pre-defined data model and whether it’s organized in a pre-defined way.
3 - Time-stamped data
A dataset which has a concept of time ordering defining the sequence that each data point was either captured (event time) or collected (processed time).
4 - Machine data
The digital exhaust created by the systems, technologies and infrastructure powering modern businesses.
5 - Spatiotemporal data
Describes both location and time for the same event -- and it can show us how phenomena in a physical location change over time.
6 - Open data
Data that is freely available to anyone in terms of its use and rights to republish without restrictions from copyright, patents or other mechanisms of control.
7 - Dark data
Dark data is digital information that is not being used and lies dormant in some form.
8 - Real time data
The term used to refer to instantaneous computing that happens about as fast as a human can perceive.
9 - Genomics data
Data that involves analysing the DNA of patients to identify new drugs and improve care with personalized treatments.
10 - Operational data
Companies have big data, they have application logs and metrics, they have event data, and they have information from microservices applications and third parties.
11 - High-dimensional data
Data that are multi-faceted enough to be able to handle computations that are capable of describing all the nuances and individualities that exist across out facial physiognomies.
12 - Unverified outdated data
Data that has been collected, but nobody has any idea whether it's relevant, accurate or even of the right type.
13 - Translytic Data
An amalgam of ‘transact’ and ‘analyze’, translytic data is argued to enable on-demand real-time processing and reporting with new metrics not previously available at the point of action.
Source:
https://www.forbes.com/sites/adrianbridgwater/2018/07/05/the-13-types-of-data/#334731f83362