Here is the list of some common logical data models related to databases:
Hierarchical database model: The data in this data model is arranged in a tree-like structure. The data is stored in the form of records. These records are connected with links.
Network Model: It is a flexible method to represent objects, along with their relationships. Each record in a network model can have multiple child and parent records, which results in the formation of generalized graph structure.
Graph database: In this database, graph structures are utilized for semantic queries with edges, nodes, and properties for the representation and storage of data.
Relation model: It is an approach of using a language and structure to manage data. This model offers a declarative method to specify queries and data.
Enhanced Entity-Relationship Model (EER)
Also known as an extended entity-relationship model, EER was developed for reflecting the constrained and properties from complex databases in a precise manner. The examples of the complex databases include Geographic Information System (GIS), complex software programs, telecommunications, and the ones in computer aided design (CAD).
The information in this database management system is reflected as objects. The object-oriented programmers are able to develop the product and store them as objects using Object Oriented Database Management Systems (OODBMSs).
Document-oriented database: It is a computer program used to store, manage, and retrieve document-oriented information. The document databases are widely used for programming web applications.
Star Schema: This approach is commonly utilized for developing dimensional data marts and data warehouses. The physical looks like a star, which is why it is named Star Schema.
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Inverted index: Also known as inverted file, this is an index data structure that allows fast full text searches. If we are talking about document retrieval systems, this is the most popular data structure.
Flat file database: This type of database is stored in the form of an ordinary unstructured file known as a "flat file." A flat file can be either a binary file a plain text file.
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An organized collection of data is referred to as a database. The collection of reports, queries, schemas, tables, and views is referred to as relational database. A database management system is a computer program with which the users are able to interact with the database. These users can store, delete, or edit data through DBMS.
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Here we discuss different aspects of database on which we offer help.
Major Types of Databases
Database can be categorized into various types, namely:
- Data warehouse – Primary and secondary data is effectively used in data warehouse. The classification and rearrangement of data is also part of this database.
- End-user database – Data produced by end-users, such as spreadsheets and word processing files are stored in this type of database.
- Analytical database – it’s a read-only system responsible for storing historical data on various business metrics. Several professionals, like corporate executives and business analysts, use analytic database for running queries and reports.
- Hypermedia database – It is a system of computer information retrieval that lets a user access and work on various forms of data, such as text, graphics, audio-visual recordings, and photographs.
- Operational database – This database consists of event data and system-specific reference data that belongs to a transaction-update system.
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Three views of database data
Here we discuss three major views of database data that are provided by a Database Management System (DBMS):
- The external level – This defines the way the group of end-users visualize the data organization in a database. One database can have unlimited number of views at an external level.
- The conceptual level – The synthesis of every external view is offered by the conceptual level. Multiple external views are unified into a single compatible global view by the conceptual level.
- The internal level – This revolves around internal organization of data within a DBMS. It is associated with performance, scalability, cost, and related operational matters.
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