Case Study: Database Development
CIS 515 Strategic Planning for Database Systems
Dr. John Niemiec
Rashid E. Williams
The software development lifecycle encompasses a variety of different methods, designed to enhance the processes involved with designing, testing, implementing and delivering a finished and polished product to the client. While there are many different schools of thought, many would agree that each methodology provides a substantial influence and perspective on software development today. Object oriented analysis was a primary driver and catalyst in the software development industry early on due to its flexibility and capability of implementing a variety of modeling approaches. These modeling approaches included sequential waterfall like processes and iterative processes that resemble a spiral. In contrast, agile methods have become a very popular development methodology due to its collaborative and adaptive approach to development. Agile methods unlike object oriented, focuses on incremental development and revision to deliver a completed product. While these methods approach development from different perspectives, yet they share very similar philosophies in regards to the different development phases. Furthermore, both approaches are centered on planning, analysis, design, implementation and testing which I believe makes both methods useful to the enhancements of datasets. According to Rosenblatt and Shelly (2012), “Object oriented analysis views the system in terms of objects that combine data and processes. The object represents actual people, things, transactions and events” (Rosenblatt and Shelly, pg 21). Developer can enhance datasets by effectively planning, performing object oriented analysis, creating diagram and objects while utilizing use case tools to assist with identifying relationships and data dependencies. This process is very similar to that of the database development lifecycle that implements some of the very same fundamental concepts when designing a database. Planning is critical to implementing any IT project and when it comes to enhancing datasets planning is equally as important. During planning phases developers can conduct feasibility studies to identify what will be needed in regards to requirements, cost and other factors to implement each component of the dataset. Furthermore, developers can perform different analysis that looks at each component of the dataset that encompasses both data and the process. Finally, developer can create diagram and objects that depict each entity, table, classes and attributes. Theses diagrams can be used to give a visual perspective of each dataset and through iterative processes that allow designer to improve each dataset through revision.
Record selection can be optimized by using quantitative methods such as statistics to determine the pertinent information from a dataset. According to Shankaranarayanan and Even, (2009), “The purpose of the data quality measurement methodology described is to measure and understand the current quality of the evaluated dataset. It can help identify key quality issues and prioritize quality improvement efforts” (Even & Shankaranarayanan, 2009). In order to effectively optimize data selections administrators can implement statistically based query optimization algorithms. Statistical tools such as optimization algorithms look at important database characteristics such as size, number of records, average records access, number of users and can work with the DBMS to enhance retrieval speed. Retrieval speed is enhanced by only showing the user the first few row selected initially while the remaining rows are fetched while scrolling. By using statistical and quantitative methods users can experience greater response time by not having to wait while the entire data is generated....
References: Dual Assessment of Data Quality in Customer Databases, Journal of Data and Information Quality (JDIQ), Volume 1 Issue 3, December 2009, Adir Even, G, Shankaranarayanan.
Process-centered review of object oriented software development methodologies, ACM Computing Survey (CSUR), Volume 40 Issue 1, February 2008, Raman Ramsin, and Richard F. Paige.
Rosenblatt, H.J, Shell, G. B. (2012) Systems Analysis and Design
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