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Database Development
The objective of this study is to recommend three specific tasks that could be performed to improve the quality of datasets using the Software Development Life Cycle (SDLC) methodology and to recommend the actions that could be performed to optimize record selections and to improve database performance from a quantitative data quality assessment. Finally, this work will suggest three maintenance plans and three activities that could be performed in order to improve data quality. The second part of this study involves the evaluation of which method would be efficient for planning proactive concurrency control methods and lock granularities and assessment of how the selected method can be used to minimize the database security risks that may occur within a multiuser environment. Secondly, this work will analyze how the verify method can be used to plan system effectively and ensure that the number of transactions do not produce record-level locking while the database is in operation.
I. SDLC and Improving Quality of Datasets
High quality data makes the data resources of the organization more optimal for use in that it promotes both effectiveness and efficiency. Improvement of data quality using SDLC is reported to be in three categories including those of: (1) error detection...
( p. 6)
II. Recommendation of Actions to Optimize Record Selection and Improve Database Performance
Important factors that determine performance are reported to include the physical data input and output, CPU and memory storage, and the network load. ( ) Actions that can be taken to bring about the best performance include: (1) optimization of the size of the result; (2) optimization of the amount of data to be transferred to the application server from the database; (3) optimization of the number of data transfers; (4) optimization of the time required to search the database and retrieve the result set; and (5) optimization of the load on the database.
III. Three maintenance plans and three activities that could be performed in order to improve data quality
Three maintenance activities that ensure data quality include data quality assessment, data quality measure and…
Works Cited
Development Methodologies. ACM Computing Surveys, Vol. 40, No. 1, Article 3, Publication date: February 2008.
Even, A. And Shankaranarayanan (2009) Dual Assessment of Data Quality in Customer Databases. ACM Journal of Data and Information Quality, Vol. 1, No. 3, Article 15, Pub. date: December 2009.
Locks and concurrency control (2013) IBM. Retrieved from: http://publib.boulder.ibm.com/infocenter/db2luw/v9r5/index.jsp?topic=%2Fcom.ibm.db2.luw.admin.perf.doc%2Fdoc%2Fc0005266.html
Loshin, D. (2013) Five Fundamental Data Quality Practices. Pitney Bowes. Retrieved from: http://www.pbinsight.com/files/resource-library/resource-files/five_fundamental_data_quality_practices_WP.pdf
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