In this report, various articles are studied related to the topic database management system, data mining and analysis. Thee research that is carried in this report is secondary research that is analysing the data of other users. Database system is used to access the data easily and also to access the data while managing data integrity. The data remains protected when stored in database system as also offer control to manage the files from different location. It offers data independence so that data can be handled from multiple applications and all the errors could be recovered. It is a best way to impose logical as well as structural operations in the organisation.
Database management system is a system used for managing the large data sets. It provides the way to create, update, retrieve and manage the data. It serves as an interface between user and database so that data can be organised and remains easily accessible. The three main components that play an important role in data base management system are concurrency, security and integrity of data (Arasu, et. al, 2016). It offers centralised view to user by allowing access to information from anywhere. It is responsible for rolling back the data ad recovering data after failure.
From the article it was found that real time database management system offers both benefits as well as challenges. Real time database management system have advanced feature as compared to traditional method. Real time database management system faces the main issue in adapting to the change in operational environment (Arulraj and Pavlo, 2017).
A compared to traditional database system, real time database system has the ability to meet the time constraints. The correctness of an action is defined by its logical correctness as well as timeliness actions. If the time constraint is not met it can cause a huge failure to the system. If the deadlines are considered they are said to be hard core real time system. If the failure related to deadline can be considered it is called as soft real time system.
There are various activities that require access to information and their consecutive result in fixed time duration. The system that require database operations in fixed time duration it is said to be real time system (Bester, Shewell and Yates, 2018). Some of the features that have facilitated the use of database management system are maintenance of correctness and integrity. It also offers efficient access of data so that execution of queries and transaction takes place.
There are few disadvantages of using real time database system as the environment is changing rapidly (Bester, Shewell and Yates, 2018). The data that is not delivered on time becomes useless and invalid. There exists a time lag between monitoring and recording the data so that it gets delivered in correct time.
The primary goal of this is to minimize the transactions so transactions are completed within deadline. This can be achieved by using priority scheduling algorithms help in managing the deadlines, so that processes get completed on time.
Database system is used to access the data easily and also to access the data while managing data integrity. The data remains protected when stored in database system as also offer control to manage the files from different location. It offers data independence so that data can be handled from multiple applications and all the errors could be recovered. It is a best way to impose logical as well as structural operations in the organisation.
The data is stored in the warehouse that is collection of data from external sources, database and other sources (Van Aken, Pavlo Gordon and Zhang, 2017). The data consists of repetitive information and useless information is filtered and is called as data mining. Data mining or analysis can be said as a subset of business intelligence. Data analysis is mostly used to discover patterns so that future patters could be predicated.
Database management system is a concept of gathering information and related data at a single place. It facilitates ways through which information could be analysed and understanding about the business trends could be enhanced. The concept of database system is entirely different from production system (Hrle, Martin, Mohan, Spyker and Ya, 2016). Data mining is performed over database system to extract, analyse and identify the data. Data analysis on other hand uses different tools so that query in existing data could be identified. Data mining is a process of sorting the best data so that patterns could be identified and then decision are taken accordingly.
From the research, it was found that capabilities of collecting and generating data have increased rapidly (Wein, 2015). The growth of data has rapidly increased and it is important to find ways through which data can be accessed easily. To be more précised real time database system requires real time processing so that work load can be handled properly. Real time database is one that considers time slots to manage the work. It offers fast transaction and also offers quality service (Ganjam, et. al, 2016). Data analysis can be categorized as a way to extract information and then predict future trends. Data mining and data analysis is a step of knowledge discovery that aims in discovering and understanding huge amount of data. It is used to analyse the processes from different angles and then summarise it accordingly (Beach and Platt, 2017).
The research method that is used to understand these topics is analysing the research paper that covers a detail understanding of these system. The research stated that various issues faced by real time database system in recent time as it is required to finish number of transactions within deadline. In this secondary reach methods are used that cover the reports and studies by government agencies. Secondary research covers all the information that is gathered from other users. This research method saves the overall time and cost that is required collecting the data. Secondary data makes the data available freely in a cost effective way.
From the analysis it can be said, that there is an explosive growth of information thus it has become important to handle these information so that business intelligence could be improved (Laudon and Laudon, 2016). Data mining and data analysis has gained popularity for extracting the information and offering flexibility to people. It offers greater understanding of data by filtering it as per use. Data mining is a process of discovering hidden as well as useful information so that operations are done efficiently (Yunus, Krishnan, Nawi and Surin, 2017). The purpose of data mining is to invent new data by using analysis technique over large data set.
Database system is a structured and convenient way to manage and share information, real time database deals with time boundaries. Some of the properties of database system are atomicity that makes sure that transactions are either completed completely or not started. The consistency in transactions is also maintained. The main concern that was observed in real time database system was timing issues. On the other hand, it assures that consistency is maintained by considering timing constraint (chen, han and yu, 2019). Real time database assures that timely execution of transaction take place by following acid properties.
With the increasing complexity, real time database has gained popularity as the amount of transaction that need to be handled increases with time. Real time database need to deal with temporal data rather than static data (Ziauddin and Witkowski, Oracle International Corp, 2016). There are timing constraints associated in real time database and the main objective of real time database is to finish the transactions within deadline.
From all the analyses, it can be said that real time database management system is more efficient way for handling large amount of data. There is a specification of timing constraint and also improves overall timeliness. It also reduces development cost by avoiding redundant data (Hrle, et. al, 2018). The objective of real time database is to deal with time constraint and violations so that maximum benefits could be gained by completing the process within time.
Conclusion
It can be concluded from the research study that database system are widely used for handling large amount of data. It is widely used in multimedia services, e-commerce and e-business, web based services and in telecommunication system. Various articles have been reviewed on database system, data analysis and mining. It was understood that database management system and data mining is an important term for visualising the data and then taking decisions. Data mining and data analysis has gained popularity for extracting the information and offering flexibility to people. It offers greater understanding of data by filtering it as per use. There are various benefits that are gained by using database management system; it resolves the issue of data redundancy by gaining the access from anywhere.
References
Arasu, A., Babcock, B., Babu, S., Cieslewicz, J., Datar, M., Ito, K., Motwani, R., Srivastava, U. and Widom, J., 2016. Stream: The stanford data stream management system. In Data Stream Management (pp. 317-336). Springer, Berlin, Heidelberg.
Arulraj, J. and Pavlo, A., 2017, May. How to build a non-volatile memory database management system. In Proceedings of the 2017 ACM International Conference on Management of Data (pp. 1753-1758). ACM.
Beach, B. and Platt, D.C., TiVo Solutions Inc, 2017. Distributed database management system. U.S. Patent 9,552,383.
Bester, K., Shewell, M.A. and Yates, S.J., International Business Machines Corp, 2018. Automatic data purging in a database management system. U.S. Patent Application 15/346,121.
chen, M., han, j. and yu, p. (2019). [online] Nyu.edu. Available at: https://www.nyu.edu/classes/jcf/g22.3033-002/handouts/chen96data.pdf [Accessed 22 Jan. 2019].
Ganjam, K., Narasayya, V.R., Kaushik, R., Arasu, A. and Chaudhuri, S., Microsoft Corp, 2016. Integrated fuzzy joins in database management systems. U.S. Patent 9,317,544.
Hrle, N., Martin, D., Mohan, C., Sarin, S.K., Spyker, J.D. and Yao, Y., International Business Machines Corp, 2018. Data replication in a database management system. U.S. Patent Application 15/820,468.
Hrle, N., Martin, D., Mohan, C., Spyker, J.D. and Yao, Y., International Business Machines Corp, 2016. Database management system and method of operation. U.S. Patent Application 14/857,889.
Laudon, K.C. and Laudon, J.P., 2016. Management information system. Pearson Education India.
Van Aken, D., Pavlo, A., Gordon, G.J. and Zhang, B., 2017, May. Automatic database management system tuning through large-scale machine learning. In Proceedings of the 2017 ACM International Conference on Management of Data (pp. 1009-1024). ACM.
Wein, D., Sybase Inc, 2015. System and methodology providing workload management in database cluster. U.S. Patent 9,141,435.
Yunus, M.A.M., Krishnan, S.K.G., Nawi, N.M. and Surin, E.S.M., 2017. Study on Database Management System Security Issues. JOIV: International Journal on Informatics Visualization, 1(4-2), pp.192-194.
Ziauddin, M. and Witkowski, A., Oracle International Corp, 2016. Clustering a table in a relational database management system. U.S. Patent 9,430,550.
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