Examples of human-generated unstructured data:
- text files
- email
- social media
- websites
- mobile data
- media: audio files, video files, digital photos

Examples of machine-generated unstructured data:
- satellite imagery
- scientific data
- digital surveillance
- sensor data

Examples of Unstructured Data

Images for cat recognition is an example of “structured” data, because it is represented as a structured array in a computer. True/False?

A demographic dataset with statistics on different cities' population, GDP per capita, economic growth is an example of “unstructured” data because it contains data coming from different sources. True/False?

Though classification algorithms succeed in ignoring background data for the sake of efficiency, most tasks require a complete understanding of input data, and are thus more computationally expensive. Modeling a distribution with a lookup table in the absence of other processing creates issues of memory and efficiency.
These issues can be minimized through identifying and only modeling direct - and not indirect - interactions between variables, i.e. Structured Modeling.

Challenges of Unstructured Modeling

Unstructured data either does not have a pre-defined data model or is not organized in a pre-defined manner. It has internal structure but is not structured via pre-defined data models or schema. Unstructured data may be textual or non-textual, and human- or machine-generated. It may also be stored within a non-relational database like NoSQL.

University of Michigan - Ann Arbor

Data encompasses facts, figures, or information gathered for analysis, reference, or computation. It can be qualitative or quantitative and serves as the foundation for reasoning, discussion, or calculation across fields like scientific research, business, and technology. Data exists in diverse forms, including numbers, text, images, or sounds, and is processed to extract meaningful insights. In computing, data is the foundational element; all interactions revolve around reading, modifying, and creating it. Fundamentally, all computer data is stored as uniform sequences of bits, making it inherently similar regardless of its perceived form.

Data (Information)

Goodfellow, I., Bengio, Y., & Courville, A. (2016). $\mathit{Deep \ Learning.}$ MIT Press. Retrieved from [www.deeplearningbook.org](https://www.deeplearningbook.org) 

Deep Learning

Structured data is comprised of clearly defined data types whose pattern makes them easily searchable. Data may be human or machine generated as long as the data is created within an RDBMS structure. This format is eminently searchable both with human generated queries and via algorithms using type of data and field names, such as alphabetical or numeric, currency or date.

Structured Data

Unstructured Data

For CNNs, the data used usually has several channels (single channel or multichannel)  with different dimensionalities (1-D, 2-D, or 3-D). Each of these channels represent an observation of a different quantity at some point in space or time.

Data Types in CNN

Raw data, also referred to as unanalyzed data, is the initial information collected during a research study before any organization, coding, or cleaning has occurred. In psychological research, this data can take several different forms, such as completed paper-and-pencil questionnaires, digital files containing numbers or text, video recordings, or written observational notes.

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