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What is the difference between structured and unstructured data? Compare the impact of using structured versus unstructured data.

What is the difference between structured and unstructured data? Compare the impact of using structured versus unstructured data.

What is the difference between structured and unstructured data?

Structured data contains information, numeric, tables or figures in a highly standardized format that put the information in form of classification. It is meant to be specific and in a simple format that can be easily followed. Unstructured data involves a bulk of many varied types of data bundled together and stored in its original format.

A data model – a concept of how data can be stored, processed, and accessed – is required for structured data to exist. Each field is discrete and can be accessed independently or in conjunction with data from other fields thanks to a data model. Structured data has a lot of power since it allows you to easily aggregate data from different parts of the database (Zhang et al., 2020). Because the early versions of database management systems (DBMS) could store, process, and access structured data, structured data is considered the most “conventional” kind of data storage.

In contrast, unstructured data is information that lacks a predefined data model or is not organized in a predefined way. The data is typically text-heavy, but it may also include data such as dates, numbers, and facts. This causes irregularities and ambiguities that make traditional programs difficult to understand when compared to data stored in structured databases (Tayefi et al., 2021). Unstructured data is commonly represented by audio and video files, as well as No-SQL databases.

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Also Read: HCI 660 Benchmark – Health Information Technologies

In recent years, there has been a significant increase in the ability to store and process unstructured data, with many new technologies and tools on the market that can store specialized types of unstructured data. MongoDB, for example, is designed specifically to store documents.

What is the difference between structured and unstructured data? Compare the impact of using structured versus unstructured data.

As an example, Apache Giraph is optimized for storing node-to-node relationships (Big Data Framework, 2019). Because a large portion of data in organizations is unstructured, the ability to analyze unstructured data is especially important in the context of Big Data. Consider images, videos, or PDF documents. One of the primary drivers behind Big Data’s rapid growth is the ability to extract value from unstructured data (Big Data Framework, 2019).

In conclusion, the advancement in technology has made it easier to work with the unstructured data. The big data technology provides sophisticated software solutions that make it easier to store and process big chunks of data hence easier to derive meaning out of it. In years before, structured data was one of the easiest and best way to put up data for easy consumption. However, there is also a middle ground for the two forms of data in which the data can be collected, stored and consumed in a semi-structured way. This is a hybrid of the two forms of data.

References

Big Data Framework. (2019, January 9). Data Types: Structured vs. Unstructured Data | Big Data Framework©. Big Data Framework©. https://www.bigdataframework.org/data-types-structured-vs-unstructured-data/

Tayefi, M., Ngo, P., Chomutare, T., Dalianis, H., Salvi, E., Budrionis, A., & Godtliebsen, F. (2021). Challenges and opportunities beyond structured data in analysis of electronic health records. WIREs Computational Statistics. https://doi.org/10.1002/wics.1549

Zhang, D., Yin, C., Zeng, J., Yuan, X., & Zhang, P. (2020). Combining structured and unstructured data for predictive models: a deep learning approach. BMC Medical Informatics and Decision Making, 20(1). https://doi.org/10.1186/s12911-020-01297-6

 

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