Computer Science Homework Help

No.1.

by Maham Alam –

Designing is the first and highly important step for a successful implementation of a database but even after carefully considering the designing aspects of building a database, there is still no guarantee that it’s going to work as perfect as an ideal database, because as they say “A well-designed database just works”, which means that even slightest of the slightest mistakes can cause problems, that are usually cumulative in nature and could cause misery to DBAs, developers and managers. Therefore, in my opinion the designing part of the database development is the most important factor in deciding a successful implementation (Davidson, 2019).

With the huge developments in scope and capabilities of what customers could expect from applications, it is certainly a challenge to design a perfect database. As there are thousands of databases available that have advantages or disadvantages over the others, it becomes critical to underline some key constraints that one’s database should meet before its implementation. Some general yet crucial constrains that a good quality database should have are data safety, data security, availability, performance and scalability (Elizabeth, 2018).

Data safety and security are the terms used interchangeably to highlight data protection in a database. This characteristic of a database defines that no data should be lost or put at risk at any cost. Any database that needs to be implemented must be ensured that it is free of physical and human error related data risks, moreover, the security rules of the database should be easy to set up so that if any security breach happens the DBA is notified immediately and can take care of it. For safety of the database it’s important that database should follow ACID, irrespective of its relational or non-relational characteristic. For a better available database it is highly recommended that a data cluster is used where there are multiple servers so that the database is not dependent on just one server and it has other backup servers available to ensure working of the organization in case one server goes down. Similarly for performance and scalability, even if you are feeding your database with an extraordinary amount of data, it should still be able to process it faster, hence a database should always be deployed with a decent default settings so that it recognizes any operational environment easily and adjust according to it and eventually should grow with your data and business (Elizabeth, 2018).

Other than these general constraints, special attention must be given to the documentation, for it to be used as a guide for definitions of column, table, relationships, and constraints present in the particular database. Similarly DBA should not forget normalization of databases to avoid data redundancy and proper indexing to ensure a better performance and maintenance of the database after its implementation (Davidson, 2019).

References

Davidson, L. (2019, January 23). Ten Common Database Design Mistakes. Simple Talk. https://www.red-gate.com/simple-talk/sql/database-administration/ten-common-database-design-mistakes/

Elizabeth, J. (2018, September 26). How to overcome 5 common database challenges. JAXenter. https://jaxenter.com/overcome-5-common-database-ch…

No.2.

by Mouna Konidhina

Database applications are generally used to store data in a file system database. There are many different types of databases. One of the most used database applications is the SQL database. SQL is a language and a database is built using these databases. It is a powerful platform for retrieving, processing, and maintaining data. This application is the primary application used.in the development of Big Data systems. Another approach is to combine the development of a new system by one or more independent participants or teams with the application development activities and the training of the system development team.In a production environment, database applications are usually used to manage and monitor processes on a computer. An application is an independent application program that processes a program or a file.

High availability

In database management, a system consists of a set of activities related to the production and monitoring activities in a database. These activities are executed by the database server that runs the business logic in the system. Business logic can be thought of as a series of rules and procedures and each business logic rule has to have a correspondingexecution policy and execution rules. The model is not strictly ad hoc but is intended to give an overview of several issues related to complex problem-solving.

The distributed architecture makes it easy for nodes to share resources across the network and the failure of one does not impact other nodes in the distributed network. A distributed database is not restricted to just data storage but the storage network as well. For this reason, several distributed databases are currently in development. Cloud bursting has been widely used by companies and organizations to make use of more infrastructure resources (Mascari, et al., 2019).

Data safety

One method is to store the entire document in a database and allow the user to access the data later as needed. This technique involves an intermediary such as a search engine or any data processing program. The other method is to use specialized storage media such as hard drives that store only certain types of data. This type of storage is called transactional storage. It can be used for long-term data that requires only moderate access to the storage hardware to which it has been attached, and is used only when it is not needed.

The data stored in these environments is highly available and can be easily and quickly moved and deleted. If the data is accessed outside of the organization, it is almost guaranteed that the organization’s data could be compromised by the user. The key to effective cloud deployment is the consistency of the data, in other words: where possible, the data can be reliably and reliably backed by the correct IT infrastructure (Melikhova, et al., 2019).

References

Mascari, F., Carny, F. R. P., Liptak, L., Adorni, M., Fontanet, J., Herranz, L. E., … & Kubicek15, J. (2019). FASTNET Scenarios Database Development and Status. submitted to ERMSAR.

Melikhova, E. V., Rogachev, A. F., & Skiter, N. N. (2019). Information system and database for simulation of irrigated crop growing. In Ubiquitous Computing and the Internet of Things: Prerequisites for the Development of ICT (pp. 1185-1191). Springer, Cham.

No.3.

by Laxmi Kirti Bachu

In general, let us talk initially few points on what are the types of database models that are used by developers to build software applications. They are:

Flat Model

Hierarchical Model

Network Model

Relational Model

Dimensional Model – Supporting ETL/Data Warehousing concepts.

Flat model is a two-dimensional array of systems with rows related to one another. This is a scalable feature for this structure and the least possible usage is only to store texts. In hierarchical model, data is organized as a tree like structure with one-to-many relationship between parent and children. The main drawback of this model is that it can carry only one to many relationships between nodes. On the other hand, A network model is a database model which is one of the flexible approaches representing objects and their relationships. Uniqueness of this model is its schema, is represented as a graph where relationship types are arcs and object types are nodes. Next is one of the prime models- Relational data model, which is widely used around the world for data storage and processing. This model is quite simple and comes with all the capabilities and properties required to process data with storage efficiency. Last but not the least is the Dimensional Model which supports ETL/Data Warehousing concepts with huge repositories of data maintaining history.This is one of the widely used models inorder to produce data analytics with dashboards and reporting purposes (Choudhury , 2021)

The best 3 data models picked by developers these days to build an efficient model are:

Network,relational and dimensional.Let us understand each with an example.As we know, this model addresses the problem of flexibility which is one of the biggest advantages among simplifying concepts, conformance –to- standards and promote integrity of the databases.The disadvantages include complex structure and time inefficient.Best example is building student record management system in a school.Here one student is linked with multiple subjects or departments , student id being the key.However, even though the ease of access is great,complexity is higher (Koczkodaj).

Next is the relational model which engulfs the fact that it is the one of most widely used models.As an utmost advantage is its simplicity and almost designing any kind of database management system with logical data models in tabular structures. Best examples start from any employee records management systems to ticketing systems.Best DBMS systems are: DB2/Informix Dynamic Server – IBM, Oracle,Sybase etc.It has one of the biggest disadvantages of storage which was however eventually answered by Big Data systems.

Lastsly, the third one is an extension of relational model where data is managed via facts and dimensions to extract,transform and load the data from one DBMS to the other.This handles huge data structures and volumes.Example is to manage an entire organizational DBMS with all the necessary records starting from sales to financial aspects , draw them into reports to make strategic business decisions (Al-Fedaghi)

References-

Choudhury,(2021). Investigation of model structure strategies for the advancement of machinability database systems. Global Journal of Production Research, 34(5), 1261.

Koczkodaj,(2020). Streamlining consistency of rating scales by differential development for the utilization by aggregate wise data and database systems. Diary of Intelligent and Fuzzy Systems, 37(6), 7545-7553.

Al-Fedaghi, (2020,). Modeling Business Process and Events. In Computer Science On-line Conference (pp. 366-379). Springer, Cham.

No.4.

by Mouna Konidhina – Saturday, April 17, 2021, 9:18 PM

Number of replies: 0

Traditional database processing models are designed to handle massive numbers of users in diverse locations and contexts By combining the information stored in databases with spatial data, you will be able to derive information from geographically dispersed databases that can provide answers to questions that were previously unsolved by using different levels of spatial data (Ďurech et al., 2018). Sociological Web technology is a Web technology that enables users to interact with and access information from social bookmarking, e-mail discussion boards, and bulletin boards, which are all sources of information that can be accessed by others.

Inverted file model

Inverted file model means in contrast to other file models, data are not stored inside the virtual machine directory and data storage is in the same directory as the application files or applications. In such a case, as the model starts with a hierarchal structure, each department, sub-unit or sub-program is made visible and can be accessed directly. This increases flexibility in the system as there are no functional boundaries between the modules/activities (Fricke&Asche, 2019). Disadvantages inverted file model restricts you to one archive per folder/drive. If one folder is full and a second folder is empty, only one archive will be generated. However, folders with duplicate data can also be duplicated with this method if the original data files (the ones containing the original) are saved to another folder.

Flat model

Flat model means that we represent all the points on the map in the flat space. Hence there are some lines which can be used in the model and other lines which cannot. In this way the edges of the model get smoother. We have to consider each point on the map that we want to represent on the model (Ďurech et al., 2018).These advantages include a high level of flexibility and powerful modelling capabilities. These capabilities include the ability to model complex relationships from small to large scales, to multiple product lines, and to simulate products, process characteristics, and environmental conditions with highly accurate models.Disadvantages include the following: Degree of uncertainty the value of all possible outcomes for each person is reduced as the model gets larger. Limited sampling the number of people who can be included in the model is relatively low.

Multidimensional model

Multidimensional model is a descriptive model used in business for describing process flows. It shows the process state and the possible causes for process failure with reference to the process components. A dimension is a unit dimension. Multidimensional model advantages include the following: Data and information about the object and the system can be easily extracted for analysis. Data for process modelling, including the control, can be generated. Unobtrusive and simplified multidimensional models have the advantage of reducing the effort to produce complex models(Fricke&Asche, 2019). Disadvantages include: the difficulty of defining and isolating variable dimensions the inability to explain variation associated with a single factor difficulty in linking cause and effect an absence of a consensus on cause and effect the use of multiple cause-and-effect relationships the multidimensional approach does have some advantages, however. It allows the development of a multidimensional scale which can be of real use in comparative.

References

Ďurech, J., Hanuš, J., & Ali-Lagoa, V. (2018). Asteroid models reconstructed from the Lowell Photometric Database and WISE data. Astronomy & Astrophysics, 617, A57.

Fricke, A., &Asche, H. (2019, July). Geospatial database for the generation of multidimensional virtual city models dedicated to urban analysis and decision-making. In International Conference on Computational Science and Its Applications (pp. 711-726). Springer, Cham.