CISC 215 : Database Design And Application Development! Trivia Questions Quiz

A distributed database management system (DDBMS) is designed to handle large amounts of data that is spread across multiple computer systems. It allows for the storage and processing of data in a way that is efficient and scalable. By distributing the data across multiple systems, it improves performance and reliability. Therefore, the statement that a DDBMS governs the storage and processing of logically related data over interconnected computer systems is true.

The statement is true because current distributed database management systems (DDBMS) do face challenges in terms of management and control. DDBMS involves the distribution of data across multiple locations, which can make it difficult to ensure consistency, security, and efficient coordination. Managing and controlling a distributed database requires addressing issues like data fragmentation, replication, synchronization, and transaction management. These complexities can make it challenging to maintain the integrity and performance of the distributed database system.

The statement is true because the transaction processor (TP) is indeed the software component that is responsible for requesting data in each computer. This component is responsible for initiating and managing transactions, which involve requesting and processing data from various sources. Therefore, it can be concluded that the statement is correct.

A fully distributed database management system (DBMS) is designed to handle the challenges of managing data and processing in a distributed environment. This means that it must be able to perform all the functions of a centralized DBMS, such as data storage, retrieval, and manipulation. Additionally, it must also handle the additional functions that are imposed by the distribution of data and processing, such as data replication, synchronization, and communication between different nodes in the distributed system. Therefore, the statement that a fully distributed DBMS must perform all the functions of a centralized DBMS and handle necessary functions imposed by data and processing distribution is true.

Performance transparency refers to the ability of a system to optimize and improve the efficiency of accessing remote data. By ensuring performance transparency, the system is able to identify and utilize the most cost-effective path to access remote data. This means that the system can analyze different options, such as network latency, bandwidth availability, and cost, to determine the most efficient way to retrieve data from a remote location. Therefore, the statement "Performance transparency ensures that the system finds the most cost-effective path to access remote data" is true.

A distributed database management system (DDBMS) facilitates growth by allowing the database to be spread across multiple nodes or locations. This means that as the data and workload increase, the system can scale by adding more nodes or locations to handle the additional data and workload. This distributed nature also provides fault tolerance and high availability, as if one node fails, the data can still be accessed from other nodes. Therefore, the statement that growth facilitation is an advantage of a DDBMS is true.

A distributed database management system (DBMS) needs to have validation, transformation, and mapping functions, along with other functions, in order to effectively manage and distribute data across multiple locations or nodes. These functions ensure that data is validated for accuracy, transformed into the required format, and mapped to the appropriate locations within the distributed system. Without these functions, a DBMS would not be able to effectively handle the complexities of distributed data management. Therefore, the statement is true.

Distributed processing refers to the practice of dividing the processing workload of a database between multiple physically independent sites that are connected through a network. This allows for improved performance, scalability, and fault tolerance. Therefore, the statement that distributed processing shares a database's logical processing among physically independent sites connected through a network is true.

Distributed data access refers to the ability to access data from multiple locations or business units that are geographically dispersed. In this scenario, the statement suggests that geographically dispersed business units required distributed data access, indicating that the statement is true.

The statement is true because the internet is a vast network that connects millions of computers worldwide. These computers store and share data, making the internet a repository for distributed data. Users can access and retrieve information from various sources and locations through the internet, making it a decentralized and distributed system of data storage.

To manage distributed data effectively, it is necessary to distribute copies or parts of the database processing functions to all data storage sites. This ensures that data can be accessed and processed efficiently from different locations, reducing latency and improving overall performance. By distributing the processing functions, it also enhances data availability and fault tolerance, as there are multiple copies of the functions available across different sites. Therefore, the statement is true.

A distributed database is a database that is spread across multiple locations or nodes. Each location or node contains a portion of the data, which is called a fragment. These fragments are distributed or divided among the different sections or partitions of the distributed database. Therefore, the correct term to describe the parts or portions of a distributed database is fragments.

The statement is false because one of the advantages of a distributed database management system (DDBMS) is that the data is located near the site with the highest demand, not the least demand. This allows for faster access and retrieval of data for users who need it the most.

A distributed database management system (DDBMS) does not necessarily have to be communications-media-dependent. DDBMS is designed to store and manage data across multiple computers or servers, allowing for data distribution and replication. While communication between the different nodes in the system is crucial for synchronization and data consistency, the choice of communication media is not a requirement. DDBMS can utilize various communication technologies such as Ethernet, Wi-Fi, or even satellite links, depending on the specific requirements and infrastructure of the system. Therefore, the statement is false.

This statement is false because distributed processing and distributed databases are closely related and often used together in modern computing systems. Distributed processing refers to the use of multiple computers or processors to perform tasks simultaneously, which often requires a distributed database to store and manage the data being processed. In a distributed database, data is stored across multiple locations or nodes, and distributed processing is used to access and manipulate that data. Therefore, distributed processing usually requires a distributed database, and a distributed database often requires distributed processing.

Distribution transparency refers to the ability to manage a physically dispersed database as if it were centralized. This means that users and applications can access and manipulate the data without being aware of its distribution across multiple locations. With distribution transparency, the complexity of managing a distributed database is hidden from users, allowing them to interact with the database as if it were a single, centralized entity.

A disadvantage of a distributed database management system (DDBMS) is that there is a lack of standards. This means that there may not be consistent guidelines or protocols for how the system operates across different sites or locations. This can lead to compatibility issues, difficulty in integrating different systems, and a lack of uniformity in data management and access methods. It can also make it challenging to ensure data integrity and security across the distributed system.

Centralized database management can become problematic when there is a growing number of remote locations. As the number of remote locations increases, it becomes challenging to maintain and operate small database systems at each location. This can lead to issues such as data inconsistency, difficulty in data synchronization, and increased network traffic. Additionally, managing a centralized database across multiple sites can create dependencies and potential bottlenecks. Therefore, a growing number of remote locations can pose challenges to the centralized management of a database.

In the given statement, it is mentioned that rapid ad hoc data became unnecessary in the quick-response decision-making environment. This implies that in a quick-response decision-making environment, there is still a need for rapid ad hoc data. Therefore, the correct answer is False, as it contradicts the statement.

An unreplicated database stores each database fragment at a single site, meaning that there is no duplication or replication of the data across multiple sites. This can be useful in certain scenarios where data consistency is not a critical requirement, or where the cost of replicating the data outweighs the benefits. However, it also means that if the site where the data is stored goes down or becomes unavailable, the data will not be accessible until the site is restored.

Fragmentation is the correct answer because it refers to the highest level of transparency in which the end-user or programmer does not need to know that a database is partitioned. Fragmentation involves dividing a database into smaller, more manageable pieces called fragments, which can be stored in different locations or servers. This allows for better performance and scalability, as the system can distribute the workload across multiple fragments. Therefore, fragmentation provides the highest level of transparency by hiding the partitioning details from the end-user or programmer.

A remote request allows a single SQL statement to access the data that are to be processed by a single remote database processor. This means that instead of executing the SQL statement locally, it is sent to a remote database processor for processing and retrieving the necessary data. This is useful in cases where the data needed for processing is located in a different database system or on a different server.

In the given scenario, the correct answer is multiple-site processing, single-site data. This means that processing activities are carried out at multiple locations, but all record and file-locking activities are performed at a single end-user location. This approach allows for distributed processing while maintaining data integrity and consistency by centralizing the locking mechanisms.

The given statement is false. A transaction processor (TP) is not the software component residing on each computer that stores and retrieves data located at the site. Instead, a TP is a component of a distributed system that manages and coordinates transactions across multiple computers or nodes. It ensures that all the operations within a transaction are executed successfully or none of them are.

Network latency refers to the delay or time taken for a data packet to travel from one point to another in a network. It is the time it takes for a packet to make a round trip from point A to point B. This delay can be caused by various factors such as the distance between the two points, the congestion in the network, the processing time at intermediate nodes, or the speed of the transmission medium. Network latency can affect the performance and responsiveness of network applications and services.

Distributed processing does not require an existing distributed database because distributed processing refers to the use of multiple computers or processors to perform tasks or process data. It involves breaking down a task into smaller parts and distributing them across different machines or components. While a distributed database can be used in distributed processing, it is not a requirement. Distributed processing can be implemented without a distributed database by simply distributing the processing tasks across multiple sites or components connected through a network. Therefore, an existing distributed database is not necessary for distributed processing.

A distributed database management system (DDBMS) does not necessarily provide an advantage in terms of security. While it is true that a DDBMS can offer improved availability and fault tolerance, security is not inherently guaranteed by its distributed nature. Security measures such as access controls, encryption, and authentication must still be implemented to ensure the protection of data in a DDBMS. Therefore, the statement that security is an advantage of a DDBMS is false.

In the single-site processing, single-site data (SPSD) scenario, the processing is not necessarily done on the end user's side of the system. It could be done on a centralized server or on a cloud-based platform. Therefore, the statement is false.