Database design and management are core subjects in any computer science & web development course program. The key principles and concepts in database management build upon the concepts & ideas of data structures, data modelling, and data engineering, & are crucial for every student to master.
This database management assignment help article offers a quick refresher on the central concepts and principles of database management.
The Data Models of Databases
Data models are akin to conceptual modelling of the structure of a database. They define the techniques and processes used to achieve data abstraction at different layers of the DBMS architecture. Database models highlight the most important features, define rudimentary operations such as storage & retrieval & hide all unessential details.
Designers use data models to look at the dynamic aspects & behaviour of the system and define certain valid operations on data objects.
Database models can be categorized into:
- High-level or conceptual models: Represent data closer to normal human perception
- Low-level or physical models: Describe data as they are stored on computers; easily executable and generally defines access paths explicitly
- Relational model: The most widely accepted model where all data is stored relative to certain attributes
- The Object-Oriented model: Uses the concepts of the object-oriented programming paradigm to define data as objects along with their properties; it can easily store non-relational data.
- Entity-Relationship model: A high-level data modelling technique where entity relationship diagrams are used to develop a conceptual view of the data stored.
There are many other models besides the popular ones above, the key among which are the document-oriented, object-relational, and associative & context data models.
The Basic DBMS Architecture
The general architecture of most database systems in existence comprises three layers.
- The Internal or Physical Level: This level defines the physical schema, that is, the details of how data is stored in the storage media of a computer system. It described the type of files stored (linked lists, hash, binary trees, etc.) as well as records of their layout.
- The Conceptual or Logical Level: It lies above the physical level and defines the logical abstraction of the database. It makes storage, retrieval, and all other kinds of data operations easier by defining relationships, identifying properties & constraints, and representing semantic as well as security & integrity information.
- The External or View Level: This is the user’s view of the database and varies per the user interface. Allows users to access data in a manner that is customized to their requirements.
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We wrap up this write-up with a quick overview of the major approaches to effective database management.
Different Approaches to Modern Database Management
While relational databases dominate the market, new and more effective database management approaches have emerged in recent times. As the amount of data, the number of users, and the complexity of operations increase exponentially, the need for advanced, scalable, more capable, and resilient DBMS becomes essential.
Here are some other prominent approaches to modern database management.
Distributed Databases
Distributed databases have a single logical interface but are distributed physically across multiple locations. They are all networked together and use special distributed database management systems to store and work with data across various locations.
Client/Server Databases
Client/server databases act as excellent alternatives to file servers. These databases follow the client-server networking model with the DBMS application running on servers. Clients request data from the database server, which returns the necessary information.
Client-server databases reduce the load on a network and speed up data traversal.
Data Warehouses
The rise of big data necessitated the design and development of data warehouses. Data warehouses are capable of storing and organizing diverse kinds of data. They can keep a heterogeneous mix of data, subject-oriented, time-variant and designed to aid in analytics & different kinds of decision-making processes.
Data warehouses organize data according to nature and generally amalgamate information from different sources or databases. Data warehouses are integral components of any enterprise-level data analytics system.
Well, that’s all the space we have for this article. Hope this article helped refresh your concepts & ideas. Study hard, solve problems, and ace your assignments with expert aid from academic writing service.
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