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Structured, Semi-Structured, and Unstructured Data for Cinescape’s Business Intelligence Case Study

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Structured Decisions at Cinescape

An example of structured data could be any summaries of movies that a movie theatre stores. Any artistic creation can be divided and defined into a specific category depending on the genre, the length of the tape, or the ratings of critics. Structured data is the easiest to classify and categorize as it has specific distinct characteristics. This information storage is one of the most common types today because it provides fast search and access to files.

Semi-Structured Decisions at Cinescape

Cinescape can use semi-structured data for information that cannot be stored in relational databases. The possibilities of distribution of semi-structured data arrays are determined by the selection of specific programs that can isolate general categories for them. At the same time, such data has some properties by which they can be sorted and therefore are called semi-structured. A company may use this type to store software such as XML or logs of various programs.

Unstructured Decisions at Cinescape

Unstructured data has no predefined parameters and cannot be viewed in terms of specific categories. Cinescape can use this structure to store various text files, such as customer base or other company documents. This type of data cannot be fully processed, since each file contains additional information and, accordingly, significant computing power is required. Such data cannot be sorted into categories, so more modern technical solutions are required for storage.

Role of Business Intelligence in Decision-Making

Business intelligence (BI) can help answer these questions by helping you make informed business decisions. This algorithm can analyze different datasets much faster than humans and categorize them accordingly if possible. This program can explain the technique of specific files and their classification by analyzing the content and comparing it with other explicit files in the system (Kuwait University, n.d.). To respond to the proposed unstructured BI solutions, information about the type of data being analyzed will be required.

Reference

Kuwait University. (n. d.). Cinescape online booking system.

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IvyPanda. (2025, August 26). Structured, Semi-Structured, and Unstructured Data for Cinescape’s Business Intelligence. https://ivypanda.com/essays/structured-semi-structured-and-unstructured-data-for-cinescapes-business-intelligence/

Work Cited

"Structured, Semi-Structured, and Unstructured Data for Cinescape’s Business Intelligence." IvyPanda, 26 Aug. 2025, ivypanda.com/essays/structured-semi-structured-and-unstructured-data-for-cinescapes-business-intelligence/.

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IvyPanda. (2025) 'Structured, Semi-Structured, and Unstructured Data for Cinescape’s Business Intelligence'. 26 August.

References

IvyPanda. 2025. "Structured, Semi-Structured, and Unstructured Data for Cinescape’s Business Intelligence." August 26, 2025. https://ivypanda.com/essays/structured-semi-structured-and-unstructured-data-for-cinescapes-business-intelligence/.

1. IvyPanda. "Structured, Semi-Structured, and Unstructured Data for Cinescape’s Business Intelligence." August 26, 2025. https://ivypanda.com/essays/structured-semi-structured-and-unstructured-data-for-cinescapes-business-intelligence/.


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IvyPanda. "Structured, Semi-Structured, and Unstructured Data for Cinescape’s Business Intelligence." August 26, 2025. https://ivypanda.com/essays/structured-semi-structured-and-unstructured-data-for-cinescapes-business-intelligence/.

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