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Sudipto Chattopadhyay

Discuss the distinction between centralized and decentralized conceptual database design:.

Centralized and decentralized design constitute variations on the bottom‑up and top‑down approaches we discussed in the third question presented in the discussion focus. Basically, the centralized approach is best suited to relatively small and simple databases that lend themselves well to a bird's‑eye view of the entire database. Such databases may be designed by a single person or by a small and informally constituted design team. The company operations and the scope of its problems are sufficiently limited to enable the designer(s) to perform all of the necessary database design tasks:

1. Define the problem(s).

2. Create the conceptual design.

3. Verify the conceptual design with all user views.

4. Define all system processes and data constraints.

5. Assure that the database design will comply with all achievable end user requirements.

The centralized design procedure thus yields the design summary shown in Figure Q6.6A.


Figure Q6.6A The Centralized Design Procedure

Note that the centralized design approach requires the completion and validation of a single conceptual design.


Note: Figures 6.15 and 6.16 contrast the two design approaches, Figure 6.6 shows the procedure flows; demonstrate that such procedure flows are independent of the degree of centralization.

In contrast, when company operations are spread across multiple operational sites or when the database has multiple entities that are subject to complex relations, the best approach is often based on the decentralized design.

Typically, a decentralized design requires that the design task be divided into multiple modules, each one of which is assigned to a design team. The design team activities are coordinated by the lead designer, who must aggregate the design teams' efforts.

Since each team focuses on modeling a subset of the system, the definition of boundaries and the interrelation between data subsets must be very precise. Each team creates a conceptual data model corresponding to the subset being modeled. Each conceptual model is then verified individually against the user views, processes, and constraints for each of the modules. After the verification process has been completed, all modules are integrated in one conceptual model.

Since the data dictionary describes the characteristics of all the objects within the conceptual data model, it plays a vital role in the integration process. Naturally, after the subsets have been aggregated into a larger conceptual model, the lead designer must verify that the combined conceptual model is still able to support all the required transactions. Thus the decentralized design activities may be summarized as shown in Figure Q6.6B.


Figure Q6.6B The Decentralized Design Procedure

Keep in mind that the aggregation process requires the lead designer to assemble a single model in which various aggregation problems must be addressed:

¨ synonyms and homonyms. Different departments may know the same object by differentnames (synonyms), or they may use the samename to address differentobjects(homonyms.) The object may be an entity, an attribute, or a relationship.

¨ entity and entity subclasses. An entity subset may be viewed as a separate entity by one or more departments. The designer must integrate such subclasses into a higher‑level entity.

¨ Conflicting object definitions. Attributes may be recorded as different types (character, numeric), or different domains may be defined for the same attribute. Constraint definitions, too, may vary. The designer must remove such conflicts from the model.

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5d ago

Centralized DBMS stores all data in a single location, making it easier to manage but prone to single points of failure. Distributed DBMS spreads data across multiple locations for improved scalability and fault tolerance, but requires more complex management to ensure data consistency and coordination among different sites.

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Q: What are the differences between centralized and distributed DBMS?
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What are distributed-databases in dbms?

Distributed databases in a DBMS are databases that are stored on multiple computers across a network. They allow for data to be spread out and accessed simultaneously from different locations, which can improve performance and scalability. Distributed databases can enhance fault tolerance and reduce the risk of data loss.


What is query processor in distributed dbms?

The query processor in a distributed DBMS is responsible for receiving and analyzing queries from users or applications, determining how to execute the query across multiple distributed nodes, and coordinating the execution of the query to retrieve the desired data efficiently. It optimizes query performance by considering factors such as data distribution, network latency, and data transfer costs across distributed nodes.


Why fragmentation and date replication are useful in Distributed DBMS?

Fragmentation and data replication are useful in Distributed DBMS for various reasons. Fragmentation helps in breaking a large database into smaller fragments that can be stored on different nodes, improving data access and query processing speed. It also enables data distribution and parallel processing, which can enhance overall system performance. Data replication, on the other hand, involves creating multiple copies of data on different nodes. This ensures data availability and fault tolerance, as if one copy becomes unavailable, the system can retrieve data from other replicas. It also enables load balancing and improves data accessibility in a distributed environment.


Differences between relational database management system and database management system?

A relational database management system (RDBMS) is a type of DBMS that stores data in a structured format using tables with rows and columns, and enforces relationships between data. A DBMS, on the other hand, is a broader term that encompasses various systems for managing databases, including relational, object-oriented, and NoSQL databases. In summary, an RDBMS is a specific type of DBMS that organizes data in a relational model.


What are three types of dbms?

Three types of DBMS (Database Management Systems) include relational DBMS, object-oriented DBMS, and NoSQL DBMS. Relational DBMS organizes data into tables with rows and columns, object-oriented DBMS stores data as objects and classes, and NoSQL DBMS handles unstructured and semi-structured data with flexible schemas.

Related questions

What are distributed-databases in dbms?

Distributed databases in a DBMS are databases that are stored on multiple computers across a network. They allow for data to be spread out and accessed simultaneously from different locations, which can improve performance and scalability. Distributed databases can enhance fault tolerance and reduce the risk of data loss.


What is centralized database?

Distributed and Centralized Databases Distributed data is defined as collection of logically distributed database which are connected with each other through a network. A distributed database management system is used for managing distributed database. Each side has its own database and operating system.A centralized database has all its data on one place. As it is totally different from distributed database which has data on different places. In centralized database as all the data reside on one place so problem of bottle-neck can occur, and data availability is not efficient as in distributed database. Let me define some advantages of distributed database, it will clear the difference between centralized and distributed database.Users can issue commands from any location to access data and it does not affect the working of database. Distributed database allows us to store one copy of data at different locations. Its advantage is that if a user wants to access data then the nearest site (location) will provide data so it takes less time.There are multiple sites (computers) in a distributed database so if one site fails then system will not be useless, because other sites can do their job because as I earlier said that same copy of data is installed on every location. You will not find this thing in centralized database.Any time new nodes (computers) can be added to the network without any difficulty.Users do not know about the physical storage of data and it is known as distribution transparency, as we know that ideally, a DBMS must not show the details of where each file is stored or we can say that a DBMS should be distribution transparent.


Explain the centralized DBMS architecture in detail?

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The execution of a user program which interacts with the distributed DBMS ia called?

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DBMS used in web-based application?

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What is the use of dbms?

DataBase Management System (DBMS)is a software package# it allows data to be effectively stored, retrieved and manipulatedand # the data stored in a DBMS packege can be accessed by multiple users and by multiple application programs like (SQL Server, Oracle, Ms-Access) .Types of DBMS# Hierarachical DBMS (HDBMS)# Network DBMS (NDBMS)# Relational DBMS (RDBMS)# Object Oriented DataBase(OODB)# Distributed DBMS (DDBMS)


Explain the link between hardware and application software?

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What is query processor in distributed dbms?

The query processor in a distributed DBMS is responsible for receiving and analyzing queries from users or applications, determining how to execute the query across multiple distributed nodes, and coordinating the execution of the query to retrieve the desired data efficiently. It optimizes query performance by considering factors such as data distribution, network latency, and data transfer costs across distributed nodes.


What is the difference between a desktop DBMS and a general DBMS?

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What are the differences between database management system Vs relational dbms?

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Why global query optimization is difficult in distributed dbms?

1:parallel execution 2: Additional communication cost 3: Transparency and replication