Day 12: Data Models

Hello Dear Students,
  Hope you all are doing good...

Today we are going to cover the topic of data modelling.

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DATA MODEL - Data model also known as Database Model describes the data nature such as-
  • It describes how the data is to be arranged
  • It describes what information is in the database.
  • It describes how the database is related with each other means their relationships.
  • It also describes that how the data will be used. 

The data model basic components are-
  1. Entities - Entities are the objects about which the data is collected, such as Employee, Customers, whose data is being collected in the database.
  2. Attributes - Attributes are the characteristics of these entities such as Employee_ID, Customer_Name, etc. 
  3. Relationships - Relationships are the association between 2 or more entities, that how the entities are related with each other. Relationships can be one-to-one, one-to-many, many-to-one, many-to-many. For example, Author writes Book. Here relation is writes which tells the relation between entities, Author and Book.
  4. Constraints - Constraints are basically the restrictions on the data according to the requirements. The constraints can be- Key constraints, Integrity constraints, domain constraints and so on. Example, The Employee_ID not null, means the Employee_ID must be filled and not left as blank.

TYPES OF DATA MODELS - Basically there are 3 categories -

  • OBJECT BASED DATA MODELS - This is also known as conceptual model in which the entities, attributes, and relationships are concerned. These models describes data at logical and the user-view level. It also specifies various constraints on the data as well. The object based models are as follows- 
  1. Entity Relationship Model - This model describes the database structure graphically. It is easy to use and understand as it is graphical.
  2. Object Oriented Model - This model describes the objects which forms a class. This model is basically represented graphically with the object diagram containing object classes.For example, Versant, FastObjects.Net etc. uses this model.
  3. Semantic Data Model - This model organizes the knowledge and not the data. Semantics means the meanings basically concerned with the Artificial Intelligence. In coming times, DBMS will be partially or fully intelligent.
  4. Functional Data Model - This model describes the computations within the system. It basically consists of the data flow diagrams. 

  • RECORD BASED DATA MODELS - This is also known as Representational Data Models. These models describes data by using the records structure(fixed record, fixed no.of fields, fixed length). The record based models are as follows -
  1. Hierarchical Model - This model describes the data in a tree structure i.e. hierarchy of parent and child records, and is basically the top-to-bottom approach. It was the oldest model, and introduced by IBM's Information Management System. 
  2. Network Model - This model is a many to many model which is in the form of links/graphs. The directed graphs are used and not the tree structure. It was also oldest model, and designed to handle non-hierarchical relationships.
  3. Relational Model - This model was introduced by Dr. EF Codd. It basically describes the data in the form of tables(which are called relations). The tables rows are known as Tuples and the table columns are called Attributes. It basically consists of many tables which can be interrelated with each other.

  • PHYSICAL DATA MODELS - These models specifies that how the data is stored in the physical computer along with their records, ordering and paths. These are operated by specialized users only. The physical models are as follows-
  1. Unifying Model 
  2. Frame Memory Models

Some enhanced data models are as follows-

  • TEMPORAL DATABASE - The temporal database basically includes the time property. The database changes according to the time, the temporal database stores the data according to the time instances. Example, add the date to each database so that it can be easily identified that this database is on that date and time. It basically stores all the past, present or the future times. It represents the time period with no end(infinity). For example, at hospitals, temporal database is used and the system records all the reports of the patients on proper time and date. It is widely in use. The various applications of temporal database are as follow-
  1. Health Care
  2. Banking
  3. Finance
  4. Insurance, and so on..
Temporal Database important terminologies -
  1. Valid Time (VT) - VT is the time on which something true happens and not the technical. For an example, If an employee joins a job on 30 April 2019 and quits the job on 15 march 2020, but it's record from the database is deleted on 30 march 2020. Then, the VT would be from 30 April 2019 to 15 march 2020 and not 30 march 2020.
  2. Transaction Time (TT) - TT is the time on which a transaction is being made on the database. Foe example, in above example, the transaction takes place on 30 march 2020, then the TT will be on 30 march 2020, a single date.
  3. Bi-temporal Time (BT) - The bi temporal time is the combination of the VT and the TT.

  • MULTIMEDIA DATABASE - The word multimedia comprises of 2 words, Multi and Media , Multi means many and Media means medium. Multimedia basically means the data or information being represented in many mediums such as 
  1. Text - .doc files. Text documents
  2. Images - .jpg, .png. The images
  3. Audio - .mp3, .ogg. The audio files
  4. Video -  .mp4, .avi. The video format files.
  5. Animation, Graphics, and so on..
The database in which the multimedia formats are there on the database is known as the multimedia database. 

  • DEDUCTIVE DATABASE - A deductive database is a database system that can make deductions, that is conclude additional facts based on facts and rules which are stored in a deductive database. A language which is used to define the facts in deductive database is"Datalog".It is most expressive than Relational Database. The deductive database found new application for-
  1. data integration
  2. information extraction
  3. networking
  4. program analysis
  5. security
  6. cloud computing.

  • DISTRIBUTED DATABASE - The distributed database refers to the database which is divided among various branches. The data is being divided and provided on various branches of computers and it is not centralized. The data can be provided easily at any location computer without being centralized. The software which is used to manage the distributed database is known as Distributed Database Management System (DDBMS). The remote computers are there which stores the database and provide when needed.

  • CENTRALIZED DATABASE - The centralized database refers to the database in which there is a controller physical computer database and all the information is provided from that one system. The various remote computers are there but they are connected with that one centralized system. The main disadvantage is that if the centralized system gets fail, then the whole procedure/system fails. The insertion/deletion/modification operations are performed on the centralized database.

  • MOBILE DATABASE -  The mobile database is the database which is connected by our mobile phones over a mobile network. When we work on our laptop, PCs, we use basically the mobile database which is capable of communicating with the database server and the remote sites which are allowed for the communication or transmission of data from the database. 

  • XML AND INTERNET DATABASE - XML stands for eXtensible Markup Language, is a format basically in which the huge amount of data is stored. The XML database was developed to exchange the semi-structured documents, invoices, form applications, etc, over the Internet. XML is flexible and also easily accessible database. XML database is basically the database whose extension is XML for the conversion of XML documents. 

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