Course: Database Systems Discussion 1 (Chapter 12): Compare inheritance in the EER model (see Chapter 4) to inheritance in the OO model described in Section 12.1.5 Instructions: Your response to
Substantive replies to the below posts:
Post 1:
Ramya
Discussion-2
COLLAPSE
Top of Form
DISCUSSION 2:
Structured data: Structured data are those type of data which are stored already in order. There are nearly 20% of the total existing data are structured data. All the data generated from sensors, weblogs, are all machine-generated structured data. It concerns all data which can be stored in database SQL in a table with rows and columns. The human-generated structured data are those which are taken as information from a human. Like their names, addresses, etc. An example of structured data is a database.
Unstructured data: the unstructured data have no clear format in storage we can store structured data in the row-column database, but unstructured data cannot be stored like that. At least 80% of data are unstructured. All satellite-generated images, scientific data, or images are categorized as machine-generated unstructured data. So for Unstructured data, there are alternative platforms for storing and managing, it is increasingly prevalent in IT systems and is used by organizations in a variety of business intelligence and analytics applications. There are various types of human-generated unstructured data. These are images, videos, social media data, etc. the example of unstructured data is a text document, PDFs, images, videos, etc.
Semi-structured data: it is very difficult to categorize this type of data. Sometimes they look structured, or sometimes unstructured. So that’s why these data are known as semi-structured data. We cannot store these types of data using traditional database format, but it contains some organizational properties. With some process, you can store them in the relation database. Examples of semi-structured data are spread sheet files, XML or JSON documents, No SQL database data items, etc.
Reference:
Eshuis, R., & Kumar, A. (2016). Converting unstructured into semi-structured process models. Data & Knowledge Engineering, 101, 43–61. https://doi.org/10.1016/j.datak.2015.10.003
Bottom of Form
Post 2:
Michael Thomas
Week 5 Discussion
COLLAPSE
Top of Form
There are three types of data that can be worked with, which include: structured, semistructured, and unstructured. Structured data is stored in relational databases that usually have a strict format (Elmasri & Navathe, 2017). The database schema is meticulously designed to ensure all records follow and adhere to the same format. The database will check to make sure that all data follows the structures and constraints specified in the schema (Elmasri & Navathe, 2017). Semistructured data has no predefined schema where some attributes may exist in some entities but may not in other entities. The data will have some structure, but not all the data will have an identical structure (Elmasri & Navathe, 2017).
In contrast to structured data, semistructured data can have the schema information mixed in with the data values. Also, there is no requirement for the semistructured data to have a predefined schema where data objects must conform (Elmasri & Navathe, 2017). The final data type is unstructured data. In unstructured data, there is limited indication or information of the kind of data that exists. One such example of unstructured data is an HTML web page. The text is stored in HTML tags that tell the processor how to display the texts in the different tags. Unstructured data is quite different from semistructured and structured data as there is no format or defining schema. HTML pages can interact with databases using SQL queries, though they lack any schema information to determine data types within the HTML documents.
Reference
Elmasri, R., & Navathe, S. B. (2017). Fundamentals of database systems (7th ed.). Pearson.
Bottom of Form
