Discussion Replies: Business Information

The student must then post a reply of at least 400 words by 11:59 p.m. (ET) on Sunday of the assigned Module: Each reply must incorporate at least 1 scholarly citation in APA format. Any sources cited must have been published within the last five years.

The reply can be from any one of the paragraphs listed below but 400 words with 1 scholarly citation

Casey Conway

Why a Company Would Want a Distributed Database

A distributed database is a database spread across various locations, facilities, floors, etc., and is not limited to a singular system or site. Databases can be spread over a network comprised of multiple systems and platforms. Organizational data is accessible across each location and various network devices (Chen et al., 2012). Organizations can therefore use distributed databases to meet demand and workload requirements.

When using a distributed database, organizations can expand their current infrastructure to increase modularity. Distributed databases support modular development by adding new servers and/or applications to the existing architecture without interrupting the organization's day-to-day activities. Moreover, distributed databases increase reliability when compared to centralized databases (Amer et al., 2017). Therefore, companies should use distributed databases to improve performance and availability. Additionally, organizations should implement distributed databases to reduce administrative costs and increase response time.

Distributed databases can increase the performance and power of the network by using multiple systems to process data rather than a singular system. Through distribution, organizations can save on storage and maintenance costs. In some cases, distributed databases do not require extensive storage facilities, which are typical for centralized facilities. Additionally, distributed databases protect against disaster. In a disaster, data is stored in multiple locations and still accessible if another system becomes damaged.  

Organizations must examine their current needs to determine if a distributed database is needed. Some organizations have multiple locations and many users that need to access data simultaneously. Distributed databases are flexible and able to be expanded to accommodate growth. This model provides near-real-time improvements and can maintain the pace of modern business. Whether increasing systems, data, applications, or users, distributed systems can adapt without causing severe delays to the organization.

Discuss What is Considered an Acceptable System Response Time for Interactive Applications

According to Badam et al. (2017), the system response time has long been debated. Many suggest a response time limit of 0.1 seconds where the user feels that the system is spontaneously reacting. This means that the results are only displayed, and no unique feedback is necessary to be stated. Additionally, the 1.0 second is approximately the time limit that allows the user's flow of thought to remain uninterrupted; however, users notice the delay in most cases. Most of the time, there is no unique feedback when there is a delay that is less than 1.0 seconds but more than 0.1 seconds; however, users lose the feeling of directly operating on the data (Badam, 2017).

Several factors lead to increase rapid response times. A factor to consider is the hardware components. Hardware plays a significant role and requires elements that are tailored to meet the operational environment. Increasing the quality of components and hardware specifications results in higher processing speed. This enables each program or service residing on the network to achieve optimal performance (Nexcess, 2019).

Additionally, internet speeds factor into response time. In many cases, users expect websites to load quickly. Therefore, the response time for interactive applications must be considered.

System response time for interactive applications is the time between user requests and the completion of the task (Nexcess, 2019). Response times should be as executed and completed as fast as possible. Each system or interface, like animation, should be configured and timed according to the real-time clock (Nexcess, 2019). Meaning that it should not be timed according to the indirect effect of the computer's execution speed.

The user's attention can be kept within the limit of 10 seconds when conversing. Often, users begin to perform other tasks when response time is more than 10 seconds. Therefore, the users should be given feedback showing the current response time and when the system will complete the task. This is a significant concept, especially when experiencing increased delays. Users are waiting for a highly variable response time and are provided with minimal information (Amer et al., 2017). Therefore, where the computers cannot provide an immediate response, the user should be provided with continuous feedback in the form of a completion indicator (Mie). This should be done for any operations that take longer than 10 seconds to be executed.

Discuss the Key Characteristics of Centralized Data Processing Facilities

Centralized databases (CDB) are typically located in one specific location and the main facility that stores data and managers network activity. Examples of centralized data facilities include mainframes, servers, computers, etc. The CDB has several benefits such as data integrity, redundancy, enhance physical security, and cost. Operational environments for CDBs can include client-server relationships, thin clients, and cluster sharing. Different methods control each method and the manner of data processing (Icommunity, 2021). Each end device needs to be configured in a way that improves data processing. Centralized data processing facilities comprise a computing architecture where processing is executed on a central server (Icommunity, 2021). In this architecture, the central server's computing resources are deployed. Thus, the central server is responsible for ensuring that the logical application of all the processes is delivered to the clients' machines.

Centralized processing architecture needs specific facilities to implement the system. One or more terminals are connected to a single processor (Krishnan, 2013). A single processor controls all the connected terminals. Moreover, any command can be fulfilled by a single processor, and the operations executed and displayed on the connection terminals. Therefore, in this type of architecture, the single centralized storage area is used to store all the data collected. A single computer that has a high processing speed is used to process data. This architecture is beneficial for small organizations when consumption and collection of data are done simultaneously (Krishnan, 2013).

While centralized databases can be beneficial for some organizations, there are potential drawbacks. One drawback is the singular location. All data is stored and processed in one place, and in the event of a disaster, the organization is at risk of losing its data and network. Additionally, depending on the size of the network, a network can experience slow speeds and long delays because of network traffic. All traffic is routed to the CDB and may become overloaded (Icommunity, 2021).

Discuss the Major Types of Equipment and Communication Redundancies Found in Today's Data Centers

Architectures have been designed and used by data centers to increase the center's redundant power. In case of a utility failure due to the effects of severe weather, power line issues, or loss of equipment, the data centers with redundant power are more equipped to deal with the situation (Hasan, 2009). Redundancies are critical to data centers and reduce risks associated with outages. Examples include N+1 or N+X Data Center Architecture and 2N or 2(N+1) Data Center Architecture.

N is equal to the quantity that is needed to power the data center altogether. N+1 will give a minimal amount of reliability. It will achieve this by adding a simple component that will support any single failure or single requirement. A real-life example of the N+1 data center architecture is when the overall load of the data center is 1000 kW. Unfortunately, each UPS platform can only handle up to 500 kW. Therefore, three of the 500 kW UPS system will be used. This will make it possible for the center to deliver 1000 kW of the required UPS power (Hasan, 2009).

Unlike N, this design is a complete redundant design and mirrored system. In case two UPS(s) are needed, they would be fully independent to enhance flexibility. In this architecture, the redundant components will not necessarily require to be of a similar model. Although the redundant components may make the load much more significant, they do not necessarily need equal quantities.

Many tend to misinterpret the 2N data center architecture. They believe that any center functioning on an N+1 and at half load is a 2N design. Many centers are prone to using the 2(N+1) design to provide maximum reliability. 2(N+1) is the double amount of required capacity plus a redundant N+1 design or system. This type of redundancy can continue functioning even after some component failures. With the entire system down, the 2(N+1) architectures can maintain the N+1 redundancy (Brandao, 2018).

Although beneficial, the 2(N+1) architectures are costly for designing, operation cost, floor space, and maintenance. Therefore, many data centers tend to choose 2N, which is more flexible and easy operational management but less costly. Distributed redundancy will provide the same reliability that the 2N gives but with the N+1 operating cost and capital (Steman, 2018). It also comes with increased load management challenges. There is a high price to pay. They include capital and floor space.

In this architecture, the three available power backup systems will always be available for two server loads. A 3N/2 redundant may almost be similar to 2N+1 in a 2-server environment in terms of redundancy. However, they will differ in terms of operating cost, complexity, and flexibility. The 3N/2 could be extended to 4N/3, but only in theory. This is because four would be very difficult when managing and balancing loads to maintain redundancy. Therefore, a 4N/3 or 5N/4 system would be less reliable compared to a basic N system. Again, this is because they are very elaborate and complex systems with many components which may fail (Brandao, 2018).

Conclusion

There are many factors to consider when determining the appropriate network for your business. Size, location, and resources should all be considered when deciding which type of database is most suited for the organization. Centralized databases and distributed databases can be beneficial when implemented correctly. However, implementing a database that is not tailored for the environment can be costly and result in poor performance.