Evaluation Of User Requirement Analysis Of Data Warehouse Design

Questionnaires are also disseminated to gather opinions from end users. In addition, analysts will observe the way the current system is used to perform day-day activities, and collect data. Analysis will be conducted on the different types of documentation used to understand certain rules, processes and procedures. Finally, a joint application design (JAD) can be conduct by way of a meeting with end users. The purpose of the JAD is to gather requirements that all parties can agree on (Valacich et al,

Data Warehouse is a database which is designed to process for query and analysis rather than for transaction processing, and it is usually contains historical data derived from transaction data, but can include data from other sources while relational database optimized for online transaction which includes insertions, updates and deletion.

A user needs analysis is simply demarcated as a sanctioned process dedicated for the needs of an individual, group, or company regarding a product or some form of intellectual merchandise, equipment, or system. This analysis is not only vital to the needs of the consumers and business owners, it’s also considered priceless to the shareholders or stakeholders.

Enterprise Data Warehouses (EDW) have become the foundation of many enterprises' systems of record, serving as the catalyst of strategic initiatives encompassing Customer Relationship Management (CRM), Supply Chain Management SCM) and the pervasive adoption of analytics and Business Intelligence (BI) throughout enterprises. The role of databases continues to be an ancillary one, supporting the overall structural and data integrity of the EDW and increasing its value to the overall enterprise (Phillips, 1997). The advances made over the last decade in the areas of Extra, Transact & Load (ETL) have made it possible to create EDW frameworks and platforms more efficiently, creating greater accuracy in overall database and data warehouse performance as a result (Ballou, Tayi, 1999). The creation and use of an EDW to further drive an organization to its objectives requires that the differences between databases and data warehouses be defined, in addition to a clear, concise definition of just what data warehouse technologies are. Finally, the relationship between data warehouses and business intelligence (BI) including analytics needs analysis and validation. Each of these three areas are discussed in this analysis.

In the system requirement modelling this in be a fact gathering for information or fact finding, questions will be place to our customer such as surveys, face to face interviews so we can

The major thing that all businesses have in common is the data that they use to produce results for their clients. In order to sufficiently maintain business dealings, much of the data that is collected is to be stored in an efficient manner until ready to be used. The information is stored in a data warehouse which is a culmination of a variety of databases. These are not warehouses in a typical sense as to what a common person may think of as a physical building to house the data. The data warehouse consists of large databases that are easily accessible in order to be used for decision making procedures when the time comes (Gupta, Mathur & Modi, 2012). The information that is stored within a data warehouse is not the trivial information

The title of the paper upon which this assignment is based is The Meaning of Requirements. The paper was written by Michael A. Jackson, an independent computing consultant in London, England and visiting research professor at the Open University in the UK. He is credited with some 19 publications in the field of Requirements and Specifications alone. His fields of study also include Software Engineering and Development, Problem Frames, Information System Development and Sequential Program Design Information.

Requirements Engineering (RE) is and very important phase in the software development because it is this process that gives us a base for the overall software development process. This process gets even difficult and it requires more attention when the stakeholders are separated in different geographical location and have different languages and live different cultures. Requirements engineering deals with getting the needs of the customer understand the requirements of the system to be developed. In this process we also have to understand the constraints and adapt to those constraints during the process. Global Software Development is making the practice of requirements engineering a vital one. D. Zowghi, (2003) states that as software development has progressed today, it can be said that

"A data warehouse is a subject oriented, integrated, time variant, non-volatile collection of data in support of management 's decision making process". Source

Data Warehousing also known in many industries as an Enterprise Data Warehouse is a system that contains a central repository of integrated data, often collected from multiple sources and is used to perform data analysis enabling the creation of detailed reports that contribute significantly to a corporation’s business intelligence. Data Warehousing emerged as a result of advances in the field of information systems over the last several decades. There are two major factors that drive the need for data warehousing in most organizations. First and foremost, businesses require an integrated, company-wide view of high-quality information to maintain and improve upon their strategic position. Secondly, information systems departments must separate information from operational systems to improve performance dramatically in managing company data. Critical to the success of a Data Warehousing system, Data mining allows for companies to create customer profiles, manipulate information easily, and provide knowledgeable access to the current state of their company. However, a reality that many companies often find out the hard way is that data mining and data warehousing does not work for them. As with many new tools or technology, companies may jump on the bandwagon without fully contemplating its potential weaknesses. In order to remain competitive in today’s business world, companies should consider implementing data warehouses, but only with

ABC Industries is a diversified global organization that provides a variety of services, such as financial, technical, and manufacturing of products across the globe. Its facilities are located in Europe, Asia, and the United States with revenue of $35 billion. The company has suffered problems with its retrieving qualitative data from one source. Recommendations are to utilize a data warehouse to retrieve the data to strategize analysis, root cause of issues, and Data warehouse is one of the most important components in a Business Intelligence (BI) architecture. Inmon (2005) defines data warehouse as “a subject-oriented, integrated, time-variant, and non-volatile collection of data in support of management’s decision making process” (p. 29). According to Hoffer et al., 2007; Inmon, 2005 characterizes a data warehouse is a

Poor model for long and ongoing projects .Not suitable for the projects where requirements are at a moderate to high risk of changing. So risk and uncertainty is high with this process model.

Due to the advancement that has been realized, the amount of data being generated may be overwhelming. Many proposals on data warehouses can solve this problem and handle the complex data. However, one challenge often occurs as a result of the analysis. The terminology used by different companies in OLAP is

Firstly,I will start this topic expressing my view about the requirements requirements workflow before reading the article.Actually,i thought that requirements workflow plays an important role in developing a software product but i did not expect that it the most important area to concentrate among all other workflows and the way it effects other processes that lead to payoffs in productivity,quality and risk management.

Develop Customer Requirements : Stakeholder needs, expectations, constraints, and interfaces are collected and translated into customer requirements.