Vietnam War Essay Example | Topics and Well Written Essays - 750 words

Vietnam War - Essay Example For American troopers it was troublesome even to move in wilderness. They needed to utilize exceptional instruments like blade to move starting with one spot then onto the next. So as to get by in wilderness Americans needed to catch the entire settlements. Therefore Americans lost much in this war. The interests of the both American and Vietnamese fighters were not considered by the Vietnam War initiators. The issue lied in the way that numerous Americans were against the war just as Vietnamese. They sorted out strikes and gatherings gave to the inquiry. Different nations of the world likewise were not satisfied with what was occurring as the war, which began because of the political interests, prompted the demise of many serene residents. In addition, a considerable lot of these residents furnished American fighters with assistance. The United States didn't consider the political results of their military activities on the domain of Vietnam. As a matter of fact, the objectives of the war are as yet ambiguous. Troopers themselves couldn't comprehend what they were battling for. Vietnamese were more vulnerable as far as military powers, however they were more grounded intellectually on the grounds that they realized that they simply needed to safeguard. Today everyone thinks about the gigantic military capability of the USA: even a little kid each day can see current American military procedures and strong troopers on TV, in magazines, motion pictures, PC games. It appears that military powers of the United States can do everything: help different people groups in their battle with silencers, kill perilous fear based oppressors, carry harmony to hazardous locales and furnish them with security. The American military powers were not less ground-breaking in 1970, however they despite everything figured out how to bomb the war with little lacking state †Vietnam. In this disappointment preferences assumed not the last job. American officers were viewed as legends, the strategic which is to safeguard poor and denied. Be that as it may, War in Vietnam devastated these

How to Get an ISBN in 10 Minutes (or Less!) the Master Guide for 2019

Step by step instructions to Get an ISBN in 10 Minutes (or Less!) the Master Guide for 2019 ISBN for Self-Publishers: The Complete Guide With regards to conversations around books and distributing, we as a whole know the most energizing theme at the table: how to get an ISBN.We know not every person is excited by acquiring a sequential number however, much the same as altering and configuration, they're aâ pretty basic piece of independently publishing. Fortunately, we’re here to address the entirety of your inquiries regarding the matter. Instructions to get an ISBN: the total guide for independent publishers #pubtips What is an ISBN number?An International Standard Book Number, or ISBN, is a 13-digit code utilized as a special identifier for books. An ISBN is doled out to every version of a distribution, empowering distributers, book shops, libraries, and perusers to rapidly discover titles.An ISBN number never terminates. Indeed, even extremely old numbers with just 10 digits can be changed over into a 13-digit code with this transformation apparatus from Bowker.How to peruse an ISBNAll standard ISBNs involve five sections that disclose to us the following:The number 978 or 979 shows that the digits are a book codeThe nation or language gathering of the publicationThe publisherThe title of the publicationThe check digit - which, in a non-specialized nutshell, demonstrates that the number has been verifiedAs they are utilized by retailers for stock reasons, just writers who are wanting to print and disperse printed copies of their titles need to acquire a barcode.Is it equivalent to an ASIN numbe r?It's comparable, yet not precisely the same. ASIN number are 10-digit codes created by Amazon to recognize the items on their page - so it's like an ISBN in that regard. In any case, while ISBNs can be utilized across different book shops, ASINs on apply on the Amazon store.Additional ISBN resourcesFor more data with respect to the themes secured, here are a few connects to check out:International ISBN AgencyFrequently Asked Questions (replied by Bowker)Bowker’s Set-Up GuideNielsen InformationThere’s no off-base or right answer given that you think ahead. In the event that you have a light second one day and choose to compose and distribute a book as a purposeful venture, you can most likely shun this entire procedure and sit back and relax. In the event that you’re hoping to begin your own distributing business, at that point cautiously gauge your choices. Putting resources into an ISBN may be the shrewd wagered or a pointless one, contingent upon your object ives.

Soc Essay Example | Topics and Well Written Essays - 500 words - 1

Soc - Essay Example furthermore, said that Symbolic interactionism is an investigation of human gathering, life and direct. [Lindsay Nelson, 1998) Following this definition, this hypothesis offers ascend to the significance of understanding the importance of life and direct that prompts sexual orientation and racial imbalances. As indicated by the investigation of Corell and Ridgeway, (2004) sexual orientation imbalances can be credited to culture convictions that systematized the classification of isolating people. This conviction on classification has made an inclination of contrast of social disparity of race and sexual orientation, and bringing into the framework the different multi-faceted structures throughout everyday life. This inquiry is likewise identified with the investigation of human science of sex which is one of the parts of investigation of representative connection. 2. Knowing what you think now about how oneself is developed, how would you figure sociological advising would work? What is clinical human science? What is the present condition of clinical human science? Self is somebody’s character or a part of somebody’s character, particularly as saw by others. When there is an apparent issue on one’s self, the job of a clinical humanist is to mediate so as to encourage change. Initial a Clinical Sociologist surveys the circumstance alongside the setting of convictions and practices and attempts to give an answer for improve the circumstance. The clinical humanist can concentrate on the job of advising, (for example marriage mentoring or network mentoring). Clinical humanism has been characterized by Jan Marie Fritz as †¦Ã¢â‚¬ the utilization of the sociological point of view to encourage changes. The clinical humanist is essentially a change operator who is drenched in the client’s social world Current condition of â€Å"clinical sociology†. Dr. Imprint Foster, (n.d.) in a web article, revealed that numerous colleges have consolidated sociological practice in their educational plan, and accreditation bodies have been made for this

Data Warehouse Systems - Free Essay Example

Data Warehouse Abstract This research study is related to the importance of Data Warehouse Systems. The purpose of this research is to study the uses and roles of the Data Warehouse Systems in the business organizations; whether the data and the tools provided by this system are helpful to the users; and how the systems are being used in the organizations. In order to collect the quantitative data, the survey questionnaire is prepared and qualitative data library research method is used. According to this research, more than 90% users of this system are satisfied with its use. According to this study, the reasons behind the development and growth of Data Warehousing are the changes in the technology, changes in global economy and the innovations. Also, the characteristics, authenticity of the system and the decisions based on this system can be very well analyzed by the use of Data Warehousing. CHAPTER 1 Introduction Currently, if we discuss about the methodologies of decision support system, we find that there are various technologies and methodologies, which help the management to make a fast decision-making process. The term Data Warehousing has its own importance in the present innovative environment. The main rationale behind this research study is to identify the importance of Data Warehousing system in the organization (Clark, Jones Armstrong, 2007). According to Marakas, the aim of the Data Warehouse system is to recover, store, manage and organize the data and information that is related to a particular process and its decision (Marakas, 2003). Many changes in the global economy, level of competition, growth in the technology and innovations have led to the development and growth of the Data Warehouse system across the various business institutions. This system uses the data, which is collected from both the internal and the external sources. Due to this system, the decision maker in the organization gets a comprehensive and consistent view of the organization. Topic of the Research The research topic of study is the role of Data Warehouse System in the organization. The study also concentrates upon whether it can be implemented in an easy manner. The concept of Data Warehouse (DW) emerges from several sets of information that a user needs. The needs have arisen due to the changes in the management style of different classes of end-users, who now need organization-wide view of the information. These needs are critical to the success of the business. The decision makers are required to react quickly to missions critical needs due to rapidly changing, volatile and competitive markets (Wixom Watson, 2001). They need multi dimensional support on information. The decision makers now need information for strategic decision and not for routine operational decisions. The need for Data Warehouse is felt due to the quality and content requirement of different kinds of end users in an organization. According to Jawadekar, there are three kinds of users of information; the management, knowledge workers and operational staff (Jawadekar, 2002). It helps to know whether a critical change has taken place in the business; is the change showing any pattern? And which factors are affecting the changes and its pattern? In order to control the change and use it to business advantage, the management requires analytical information support to make strategic decisions and the main purpose of this research is to evaluate the assumption that the Data Warehouse designed to meet these needs would satisfy such requirements. Importance of the study The importance of the research lies in the fact that it not only helps us to be familiar with the role and significance of a data warehouse system in decision-making but also illuminates the reasons for the success and failure of these systems. The research will prove beneficial at the time of planning, designing and implementing the data warehouse systems. With the development of better understanding between the relationships of the needs of the users of the systems and the methodologies used to present the data, the institutions will be able to do effective planning and implementation of the data warehouse systems. Also, this knowledge will guarantee proper application and thus, the success of a data warehouse system in the organization. The research will also assist the organizational leaders and information system professionals in estimating and forecasting qualitative and quantitative returns on their investments in data warehouse systems. Purpose of the study In this research, I want to target the business personnel who are the current as well as the prospective users of the data warehouse. The data warehouse has to expand its reach not only to its current users but also aim at penetrating the markets, which are still untouched from its coverage. The selection of target respondents is based on the frequency of using Data Warehouse in the organization. With the help of this project, I want to explicate the uses and roles of Data Warehouse systems in the organization and its importance to the users. The readers would be able to analyze the characteristics, features, authenticity of the system and the decisions based on this system. The main aim behind this research study is to explain the various parameters that are associated with the Data Warehouse and its use. Research questions In the data warehouse systems, what is the role of its users? Classification of users will be done as support or management data warehouse users and medium/heavy or light data warehouse users. Are the perceived needs of the users consistent with the data which has been provided? In other words, is the information provided by the data warehouse providing satisfaction to the users? Analysis of the satisfaction will be done by examining the role of the users. Through this research, the potential users of the system will also be determined. The reasons behind not using the data warehouse systems will also be determined. Background to the Study: Data Warehouse system is an essential, critical and foundation tool for management support system. Success and growth of an organization is highly dependent upon its decision-making strategies and processes. The use of the data management system will create a path for the development of the organizational decision. There are various reasons that describe the success of the data warehouse technique in the system of data management. For example, the reasons behind the success of the data warehouse system include the perceived or actual relevance of the data in the system to the user, communication about the availability of the system, the perceived or actual ease of use of the system and the training provided on the system. The reasons of the success mentioned above can affect the establishment and use of a data warehouse system in an institution like a university or corporate organization. This research is proposed to find out the actual users of the data warehouse systems and the existence of associations between the relevance of the information presented in the system, perceived or actual data available in the data warehouse system, the tools available to retrieve the data and the role of the users. CHAPTER 2 Literature Review Summary of Articles In order to complete the research study with the help of library research methodology, I have used various journal articles for analysis and collection of data and information. In order to understand the background of the literature, I have analyzed the concept, purpose and results of the articles. Summary of some articles is as follows: Article 1: Data Warehouse Administration and Management by A. Benander, B. Benander, in 2000. The article Data warehouse Administration was written by Benander Benander in the year 2000. In this article, he concluded that the data warehouse is basically a storage area of incorporated information picked from any number and variety of data source. The size of the data warehouse is usually very large and a wide range of information can be stored for a long period (Myerson, 2001). According to them, the information related to the business like the products, sales; customers, etc. are collected and incorporated in the data warehouse. For the successful administration and management of a data warehouse, there is a need of skilled and expert persons. DWA involves the overall management of data warehouse (Benander Benander, 2000). The task of administration consists of a reliable check, tracking of data, assessment, performance replication issues and data quality. It can be recommended that the data warehouses should have a backup and recovery plan so that the data can be recovered after a critical situation. According to Anne M. Smith, a data warehouse is a separate structural design used to maintain important historical data that has been removed from operational data storage. A data warehouse provides the information by creating an incorporated folder of important, subject-oriented and historical data for analysis (Smith, 1997). Data warehouse structural design provides the long-term benefits to many companies. These benefits include competitive advantage, improved knowledge, analytical and decision-making gain, etc. Article 2: Web-Based Data Warehousing by Chen Frolick in 2000. The article Web based data warehousing was written by Chen Frolick in the year 2000. According to them in general terms, the Web based data warehousing involves reviewing, analyzing and disseminating the information extracted from a data warehouse through internet and Intranet or Extranet (Chen Frolick, 2000). The aim to start the web based data warehousing is to gain more and more popularity among organization. The web based data warehousing illustrates the organization to overcome the limitation of data warehousing. The web warehouses are designed to be ascendable because they have many users. The web users could have little technical experience because the intuitiveness should be stressed and inconveniences are minimized in the design (Matt, 1998). Web technology is a perfect method for arranging high-volume records due to their uncomplicated maintenance techniques. The web enabled data warehouse delivers the accession to decision support (Matt, 1998). If the web based data warehouses are designed properly, it would cost less than the traditional solutions. For the maximum growth and flexibility, the web based data warehousing is designed and structured (Singh Singh, 1998). According to the Ayers, the web based data warehousing is the new form of data warehousing. To resolve the drawbacks, web based data warehousing can be used. Therefore, a web based data warehouse system should be highly scalable to handle a large number of users randomly. The key to web-based data warehousing is the server based processing. Article 3: Seven Key Interventions for Data Warehouse Success by Tim Chenoweth, Karen Corral and Haluk Demirkan in 2006. According to Chenoweth, Corral Demirkan, predictable knowledge holds that having a management supporter with a strongly focused (data mart) design and restrictive tools will direct to achieve high achievement. It is observed in the case study that the overturn situation can be just equal to the successfulness (Chenoweth, Corral Demirkan, 2006). To deliver value to the organization, if the clients see the potential of the data warehouse, they can be the winners and would be able to convince management to adopt the latest techniques and technology. In the same way, the data mart approach is frequently recommended as the preferred approach due to its simplicity (Chenoweth, Corral Demirkan, 2006). It is acknowledged that the needs of the users are more important. A single data warehouse may actually be more satisfying for the clients and users, if they understand both the technology as well as the organizations business processes. Interaction of technology and social circumstances decide the success of data warehouses (Kelly, 1997). The article actually presents a new insight for the execution process as well as interventions that can lead to the achievement of goals. In todays era, data warehousing represents a significant solution to the increasing challenge. A data warehouse is a single large database that has collected relevant information from several other sources (Kelly, 1997). Article 4: Does Data Warehouse End-User Metadata Add Value? by Neil Foshay, Avinandan Mukherjee and Andrew Taylor in 2007. This article Does Data Warehouse End-User Metadata Add Value? was written by Neil Foshay, Avinandan Mukherjee and Andrew Taylor in 2007 on the basis of their research study. Presently, knowledge workers are not able to use data warehouses efficiently. Levels of adoption can be increased by the use of good quality end-user metadata. Metadata provision develops the end-user services as it helps in searching of digital documents. End-user metadata is also known as business metadata and context is added in it. Business definitions for specific data attributes are provided by end-user metadata (Dyche, 2000). Metadata is a list of information for primary data and it also identifies access to the warehouse. It makes the meaning clear and gives definitions to various terms in business and data elements. It provides users with a roadmap to the information. End-user and transformational are the two types of metadata. End-user metadata is helpful in business, as it decodes cryptic name code. After decoding, the data can be recognized and used by the end-users as data element is now meaningfully described. The end-user metadata has a positive influence on the attitudes of user and level of utilization of data warehouse. End-user metadata can be standardized and in the business, it defines the layers of metadata. End-user metadata has an application for the users who look for analysis before or after forwarding queries and specific data elements are described by it. Article 5: Web-Based Data Warehousing: Current Status and Perspective by Binshan Lin and Chang-Tseh Hsieh in 2002. This article was written by C. Hsiesh in December 2002. In this article, he analyzes the present position of the Web-based Data Warehousing and its future perspectives. The feasibility of data warehousing in businesses has increased due to the quick propagation of personal computers and the networking technologies. It started in the organizations for catering the needs of different departments. There was no coordination among them. The Internet has changed all the information delivery process within and outside the organizations. In fact, the profitability has really been enhanced due to the facilitation of customer-driven e- marketplaces, both B2C and B2B (Binshan, January 2002). In the later part, the distributed architecture was developed but it failed to provide the common metadata component, which led to the formation of legamarts. This customized version supported an incremental approach to the data warehouse. It included the common dimensions, enterprise subject areas, metrics, data sources and business rules. All of these were represented in the GMR form. The majority of the data warehouses were executed by means of multiprocessor hardware. The development of Cuypers system really helped in managing and reconciling the formal heterogeneity. Such techniques will enhance the efficiency and sophistication of the data warehouse and the search tools. It will also make the transforming of multimedia information of the target users more flexible (Binshan, January 2002). Article 6: A Framework for Developing Enterprise Data Warehouses by Ali H. Murtaza in 1998. This article was written by Murtaza in the year 1998. According to him, the enterprise data warehousing (EDW) project is generally a huge and time consuming activity. He also elucidated that in many cases; the benefits are not immediately quantifiable and need a leap of faith to rationalize it (Murtaza, 1998). It is suggested that a successful, long-lasting EDW must be elastic, extensible and incorporated. In this article, the author explained that the flexibility is concerned with the impact of new or modified business data requirements on the design of data warehouse. An enterprise data warehousing initiative is one of the most frightening projects that an organization can handle (Murtaza, 1998). For an executive sponsorship, a typical high level effort is required. The article explains that a clearly defined enterprise strategy with specific goals and objectives must be presented to the stakeholders before entering into any data warehousing journey (Barquin Ramon, 1997). In general terms, a data warehouse venture differs from technological projects. The goal of the Framework Data Warehousing is to make the activities of design, implementation, and management of data warehousing solutions easier (Barquin Ramon, 1997). According to the writer, it has been designed to provide an open structural design that can be broadened easily by the customers as well as the third-party businesses by using industry-standard technology. According to Murtaza, the difficulty in quantifying the benefits is one of the problematic issues that are faced by the project manager. Murtaza also suggested that the designed structure of the metadata and data warehouse must be scalable enough to support future changes to meet information needs and analytical requirements (Murtaza, 1998). Article 7: The Data Mart: A new approach to data warehousing by Pamela Pipe in 1997. This article the Data Mart: A new approach to data warehousing was given by Pamela Pipe in 1997. In a computerized environment, variety of data is available from various systems in the organization but all of the data does not enter into the data warehouse. His article is based on the Data Mart, which means data about data. According to the research of Pipe (1997), W.H. Inmon described that in any information system application, three types of Data Mart are created: design time, control and usage data. While designing a system, a data which describes the use of input data in the application is known as Time Metadata (Immon, 1995). The control Metadata is used by the system to produce Data Warehouse. This data is used to manage and control the process of Data Warehouse creation. For example, data hierarchy is the metadata which is required to control the business data entry into the warehouse. The usage Metadata is required by the users of the data warehouse (Pipe, 1997). In this article, Pipe summarizes that the managers of the data warehouse use the technical metadata, e.g., the sources of the data, the data cleansing or enhancement rules, and the destination of the data, etc. (Pipe, 1997). The technique of Metadata usage makes business decisions on facts and not on intuition. This is applicable to both tactical and strategic business decisions. Pipe stated that if viewed intelligently and with imaginative mind, it helps the users to sense early warning on some aspects of business, calling for business review and radical change in policy, rule and strategies. Article 8: Refreshing Data Warehouses with Near Real-Time Updates by Rahman, Nayem in 2007. In 2007, Rahman, Nayem was given an article Refreshing Data Warehouses with Near Real-Time Updates. In tactical and strategic management support system, data warehouse has proved to be the chief component (Rahman, 2007). For the analysis of the historical information, data warehouse was used in conventional decision support systems. Earlier, it was easy to keep the record of the acquired data and maintain activities on the basis of demand. During that time, batch windows were used at night when the users of the business reached home. In order to make strategic business decisions, decision makers require cutting-edge information, therefore; there is a need to refresh the data ware house many times in a day (Rahman, 2007). In near real-time decision support system, the data warehouses are reviewed by using metadata model and it also enhances the frequency of batch cycle runs. A Real Time Data Warehouse shows an analytical constituent of an enterprise or project level data stream. The data stream plays an important role, as it endures asynchronous, nonstop and multi-point deliverance of data. The movement of data is from the source of origin to all uses, which do not need any kind of staging. Once the writing of original data is completed, the movement of data takes place. The delay in time is accounted to the transport latency to send off the case of data being rendered. Respondents who perform near real-time data warehousing has increased from 2 percent to 24 percent in a period of 18 months. The complete application is reserved coherent by means of these real-time updates (Ramamritham, et al, 1996). Article 9: A Comparison of Data Warehousing Methodologies by Arun Sen and Atish P. Sinha in 2005. This article was written by Sen and Sinha in the year 2005. The article explains that the data warehousing has been quoted as the post-millennium project with highest-priority with more than half of IT executives (Sen Sinha, 2005). To support the growing market, a large number of data warehousing methodologies and apparatuses are available. A major concern for many firms is to choose a tool from various methodologies which can be easily employed in a given data warehousing project (Sen Sinha, 2005). This article evaluates and assesses various important data warehousing methodologies based on a common set of attributes. This article mainly focuses on the designing of the data warehousing methodologies that are commonly proposed (Inmon, 2002). It is assumed that the business clients have diverse goals and expectations. The data warehousing is frequently successful than a pool of data warehousing expertise in-house. The various authors explain that a common set of attributes determines the methodology, which should be used in a particular data warehousing project (Inmon, 2002). Author Inmon actually had the opinion of generating a data warehouse on a subject-by-subject area basis. According to the various authors, building a data warehouse is very difficult because it is quite a new discipline and does not offer well-established approaches and methods for the process of development (Hackney, 1997). Article 10: The Benefits of Data Warehousing: Why Some Organizations Realize Exceptional Payoffs by Hugh J. Watson, Dale L. Goodhue and Barbara H. Wixom in 2002. This article was written by H. J. Watson in the year 2002. It describes the various benefits of Data Warehousing. In the field of information system (IS), Data Warehousing is one of the key developments. Due to its varied benefits, different organizations are generating different returns, depending on its impact on the organization. The common model provided by this technique makes the analysis and reporting of data from different sources easier. By the reduced inconsistencies of analysis and reporting, the companies are able to control the cost and thus resulting into the generation of high profits. The speed of the operational system of the company is also unaffected during the retrieval of data. Thus, it saves a large part of the time of the employees and the cost of the company (Immon, 1995). Though Data Warehousing involves high cost; yet, when used effectively and efficiently, it proves to be very economic. DW enables an easy approach to required information and enhances the efficiency of various decision-making processes. It assists the applications of DSS (decision support system) like that of exception reports, trend reports and reports which demonstrate the actual performance against the goals. With the help of these reports, the management and the employees of the organization are easily able to grab the opportunities of the market and generate high returns (Watson, 2000). The customer relationship management (CRM) systems are also handled easily through it. The analysis in the article also shows that the benefits of each company can be very well distinguished on the basis of the framework of its organization. Article 11: An Empirical Investigation of the Factors Affecting Data Warehousing Success by H. Wixom and Hugh J. Watson in 2001. This article was written by Wixom and Watson in the year 2001. The data warehouse from early 1990s acts as the base for the highly developed decision support applications. The literature supporting IT implementation proposes that variety determines the success of data warehousing. There is a small empirical investigation about the factors affecting data warehousing success. Distinct characteristics are shown by the Data warehousing that may affect the significance of factors that are related to it (Wixom Watson, 2001). Through the analysis of Partial Least Squares, the results show data quality and system quality factors. Further, it was observed that support from the management and resources help in dealing with the organizational issues arising on implementation of warehouse. Other factors like user participation, resources and members of extremely-skilled project team determine the finishing of the warehouse project on time, in allocated budget and with the correct functionality. The technical issues arising from low quality and deprived development technology must be tried to overcome (Wixom and Watson, 2001). Apart from this, the other factors according to Watson Haley include use of methodology, modeling, easy understandable goals and the management of expectations. The factors like well defined business needs, support from top management and user participation help in determining the operational side of the project (Watson Haley, 1997). CHAPTER 3 Research Methodology Research Methods and Design Research is a common parlance, which refers to a search for knowledge. One could also define a research as a scientific and systematic search for pertinent information on a specific topic. In fact, the research could be defined as an art of scientific investigation. This research study is based on pre-planned steps. Appropriate result of any study is based on its quantitative and qualitative data. In order to collect the data, I will use a research methodology named Analysis of Library Data along with a survey method to analyze the human thinking about this system. Library research method or analysis of historical database is the methodology in which I will analyze the articles and studies done by other researchers in the past. This methodology is useful for my analysis because the review of previous study will provide me with a quantitative, reliable and valid data (Kothari, 2005). In order to collect the qualitative data and identify the views of users of the system, I will conduct a survey analysis. In this, a survey questionnaire will be provided to the recipients to fill out. This would help to evaluate the satisfaction level of the users about the particular system and analyze the findings of the data, which we will get from the analysis of various articles. Rationale of the Methodology The method of collecting data by the questionnaires is most extensively employed in various economic and business surveys. The rationale behind using this methodology is as follows: Its cost is low even when the universe is large and is widely spread geographically. It is free from the bias of the interviewers and answers are in respondents own words. Respondents have adequate time to give their thoughts and answers. Respondents, who are not easily approachable, can also be reached conveniently. Large samples can be made in such a way so that the results can be made more dependable and reliable. Data Collection Method By arranging the conditions for collection and analysis of data in a manner for the purpose of combining relevance to the research purpose with economy in procedure, the research planning and designing is done. The research problem in this assignment is related to the Data Warehousing and its implementation in the business organization. Currently, the issue regarding the Data Warehousing is an integral issue. Various public universities and researchers have accomplished their researches on this issue and developed various applications in this direction. In order to conduct the research analysis and collect the secondary data about this particular problem, I will collect the primary data by using the previous applications and researches on this particular problem (last 10 years). I will use the library research methodology to complete this research study. In order to collect the primary data regarding the research problem, it will be beneficial to use the survey method. A survey questionnaire will be prepared that asks questions from both the current users of the Data Warehousing and personnel that are potential users (but may either not be aware of the system or dont find it beneficial). A series of questions will be prepared to know about the roles, behavior and the advantages of this system. The questionnaire will include the questions like the benefits of the system, the tools used to access the systems, etc. (Kothari, 2005). Through the analysis of questionnaire, the satisfaction level of user can be measured by the data. Both of the research methodologies, i.e. analysis of the previous library researches and survey through questionnaire method would be beneficial for the research to clarify the problem statement of the study and to identify the various solutions to improve the applications of the Data Warehousing. In order to collect the primary data through the survey questionnaire method, a study would be conducted by taking a sample of 50 people. The age of participants is from 21 to 50. Number of people Age group 10 21-30 20 31-40 10 41-50 10 50 The primary data of this research study would completely be based on the result of this survey methodology. The questionnaire is intended to determine who is using the data warehouse systems in the organization, how they are being used, whether or not the data needs are being met with this system and how the users learned of the availability of this system. Satisfaction levels of users will be measured regarding the data in the warehouse, the tools used to access the warehouse and the communication, training and support provided for the warehouse. Limitations and Challenges with the Research Methodologies Every research method has some limitations and the researcher has to face some challenges. Some limitations, which I have already faced, are as follows: Library Research Method: Who is the original researcher: It is a well known fact that each person has a different outlook towards various events. The original research depicts the outlook of the person who has conducted it. He might be biased in disclosing some of the research issues or might have ignored some key facts. In that case, our research will not show the actual position of the problem. It will be just a photocopy of the original research. Also, a systematic presentation of data is essential for giving factual information to others and facilitating further statistical calculations and interpretations. As the original research is the base of our findings, the processes adopted by it are very important to us. Through the research processes, we will be able to make out the steps adopted by the original researcher in studying his research problem along with the logic behind them. Thus, knowing the background of the original researcher and the processes adopted by him/her will facilitate us to adjust ou r research findings accordingly. Reliability of data: The researcher should test the reliability and certain things about the historical data such as who had collected the data? What were the origins of information? Was it gathered by using appropriate and effective techniques? The time when the data and information was collected. What degree of precision was sought after and was the researcher able to achieve it? In this research analysis, the researcher is bound to find out the reliability of the previous studies. He has not used all the articles and previous studies. Suitability of the data: The data, which is suitable for one enquiry may not necessarily be found in another enquiry. Hence, it was essential for the researcher to be very careful at the time of scrutinizing various terms and definition and units of collection, which was a very time consuming task for him. Adequacy of data: If the level of accuracy achieved in data is found inadequate for the purpose of the present research, this data would be considered as inadequate and should not be used by the researcher. At the time of research, this situation was faced by him on a frequent basis because after analyzing the data, when he found that it was inadequate, all the things were vanished. The questionnaire research methodology and the data collection plan used by the researcher also have some limitation, which are as follows: Low rate of return of the duly filled in questionnaires and bias due to no-response is often indeterminate. It can be used only when respondents are educated and cooperating. The control over questionnaire may be lost once it is sent. There is an inbuilt inflexibility because of the difficulty of amending the approach once questionnaires have been dispatched. There is also a possibility of ambiguous replies or omission of replies altogether to certain questions and interpretation of omissions is difficult. It is difficult to know whether willing respondents are truly representative. This method is likely to be the slowest of all. CHAPTER 4 Findings/Result Report on Data Collection Difference between data ware house and transactional database Data ware house plays a vital role in the decision-making where as Transactional databases help the people to carry out different activities. For example, a transactional database can easily show the number of available seats on an airline flight; this can help the travel agent to book a fresh reservation and the data warehouse can show the empty seats in a historical pattern. Another difference can be made on the basis of the goal. Goal of data warehouse is to stock data designed with the help of transactional data subset. On the other hand, the goal of the transactional database is related to the storage of appropriate data linked to the business unit. A data warehouse is considered as integrated, subject-related, time-variant and nonvolatile. It lays emphasis on the concept like sales instead of the process like issuing of invoices. It consists of all pertinent information based on concept gathered from the system of multiple processing. For the speed of the operation, online transaction database has been designed in the processing business transactions. It also helps to strike a balance between the insertion of record and generation of report (Jawadekar, 2005). For day to day operations, the transactional database has been defined such as insert, delete and update system or operation. In order to avoid the redundancy, these databases are normalized highly. On the other hand, for Analytical purpose, the Data warehouse databases have been designed. The core components that describe an entity in the design of a relational database are recognized in the normalized table in the form of columns. The Other components of the same entity are shifted to the different table called as lookup tables (components having repeating values). This arrangement plays an important role as it permits the quicker processing of data while minimizing the requirements of storage (Jawadekar, 2005). Relational Database Management System and Data Warehouse In order to gain a competitive strength, Management Information System is required in every organization for the intention of handling online functions, mission control applications, and to exercise the functional and management control. In this competitive and technological environment, it is not sufficient to simply computerize the back office operations. It demands a tool to effectively handle both the transactions processing and decision processing requirement. A RDBMS is a software, which fulfills all the requirements of an organization in relation to the transaction processing, decision-making, providing quick solutions, managing the data base and information, etc. (Jawadekar, 2005). A data warehouse is a distinct part of RDBMS installation. This part contains the copies of data and information from on-line system that makes it easy for the management to take decisions. With the help of the RDBMS, the management can fulfill the requirements of both the transaction process and decision support. Data Warehouse is a special database containing large sockets of an enterprise data related to Meta data processed to a ready to use stage for decision makers for operational and analytical business analysis. It helps to follow a fast decision-making process to meet the needs of functional information system and critical needs of decision makers (Jawadekar, 2005). Types of Data Warehouse To assist responding to the users analytical questions, each of the three types of data management systems is used (Benander, et al., 2000). All of these three systems vary from the operational database. The primary function of the operational database is to support the transactions of daily business operations (Chen Frolick, 2000). To get a more flexible and faster access to several of the key information of an organization, data warehouse is used (Chen Frolick, 2000). In the later part of the discussion, we will discuss the different types of data access tools, which may be offered to the users. Operational Data Store (ODS): Basically, the operational data stores are an updated version of the files containing customer information (Benander, et al., 2000). Generally, data of 12 to 18 months is stored in the operational data stores so as to restrict the trend analysis of the data held there. It is particularly used to respond to the questions on the current operations. In the organization, the users at all levels can use an operational database (Benander, et al., 2000). To summarize the current operational data at a thorough level, the use of operational data stores (ODS) is made. Normally, only the tabulation of current data is done by the ODS and no historical information is stored by the ODS. It has been seen in many cases that for performing and allowing the data queries, the legacy systems of the institution are not set up efficiently, easily and effectively. With the help of operational data store, the users can inquire about the current data for the purpose of decision-making. The decisions, which are made by making the use of the operational data store, are the day-to-day and tactical decisions. Pipe states that the institutions, which organize an ODS, could develop that data warehouse into an enterprise data warehouse at some later time period (Pipe, 1997). Data Mart (DM): The database repositories, which are designed for only one subject or functional area, like that of a human resource or finance, are known as the Data Marts. The scope of data mart is larger than the scope of operational data stores in which the information related to many years is stored, but they are not larger than the data warehouses, which have multiple functional areas. Typically, the data mart is used for providing decision support on specific subject area or to some specific department (Benander, et al., 2000). It is possible that in some cases, the data marts are first implemented in the institutions and then only the data will be put together to form an enterprise data warehouse. While in other cases, the reverse will be done. First the enterprise data warehouse will be established and then with the help of this data warehouse, the data mart will be implemented (Benander, et al., 2000). The execution of a data mart decreases the development time and the cost , when compared to a full enterprise data warehouse (Chen Frolick, 2000). Adding up, the complexity of an enterprise data warehouse can be reduced with the help of the data mart by rendering a part of the data, which has been tailored to meet the exact user requirements (Chenoweth, et al., 2006). Coskun and Pohlen, emphasized and brought into light some of the disadvantages of an enterprise data warehouse in comparison to the data mart. They said that an enterprise data warehouse required long time for its development and also involved high cost (Coskun Pohlen, 2002). While the data marts are quicker to implement and less costly, they also have the ability to carry specific data analyses (Coskun Pohlen, 2002). The data about a particular functional area or unit is contained in each data mart. As the data across the functional units and areas are not integrated, the data analysis to the functional areas cannot be done. Taking an example of the university setting, to study the cost per credit hour, there will be a requirement of integrating the data of students, financial and human resources. Credit hours will be known by looking at the student data. Data related to the departments of the faculty offering those credit hours will be provided by the human resource data; and the expenditures on those faculties and some other non-personal expenditures related with providing those credit hours is known through the financial data. The data in the data mart may be at a detailed level or a summary and comprises of data of several months and years. Though its scope is limited to particular unit or functional area, yet it allows the trend analysis. Enterprise Data Warehouse: The span and quantity of information incorporated in a data warehouse helps in distinguishing it from a data mart and an operational data store (ODS) (Benander, et al., 2000). It includes the data, which contains information of multiple years and crosses the functional areas, like human resources, students and finance (Benander, et al., 2000). In many cases, the end users will not be able to access the enterprise data warehouse because of the presence of many complexities (Benander, et al., 2000). In order to help the corporations in assembling huge quantity of data, the data warehouses were developed. Due to alterations in the market and its effects on the business, together with the changing purchasing behaviors, consumption patterns, market saturation, growing competition, difficulty in differentiating the product line and emerging markets, the need for quick generation of information is growing (Coskun Pohlen, 2002). The need for analytical databases along with the transactional databases has been created because of all the above factors (Coskun Pohlen, 2002). The above mentioned data must be transformed into managerial information so that it can be easily retrieved and analyzed. In order to support decision-making, the data warehouse acts as a vehicle for summarizing and transforming the information (Coskun Pohlen, 2002). The data warehouses, which contain data from the legacy systems, do not support the easy analysis and summarization of data. Thus, the data warehouse puts together all the data for answering the queries of multiple end-users (Coskin Pohlen, 2002). Data across the institutions are integrated by the data warehouse. In the example of the university settings, the data would include information of the students, human resources, fianc and alumni. The figure also illustrates it well. This data may also contain important information related to the strategic decision-making and the space being used by the university. All of these functional areas could be interconnected. To obtain additional details, the user may use drill-down technology. It includes both the historical and current data so that the institutions can have a look at the trends over the time period. The data ware house allows the accessibility of multi-year data. Data Warehouse Access tools To measure the perceived usefulness of information technology systems, Fred Davis did a study of two scales in the year 1989. It was supposed that both these factors had an effect on the users acceptance of the user technology (Adams, Nelson and Todd, 1992). In 1992, the study report was repeated by Adams, Nelson, and Todd to study the mental attitude of users toward messaging technology through both voice and electronic mail. It was also used to analyze the attitude of customers toward word spreadsheets, graphics and processing. The studies carried by them showed that these scales were effectual in evaluating the significance of easiness to use. These factors are important in determining the use of system (Adams, et al., 1992). The studies also distinguish that there may be some execution factors that determine the use of technology; for example training, support, user involvement, and user expectations. These factors may determine the assessment of the value of the technology. The proposal conducted through the research study will look at the users perceptions of the usefulness and ease of the use of the tools, which are available for accessing the data mart, data warehouse and operational data stores at the place of university. The scales designed by Nelson, et al., will be applied in the survey that is conducted. It was indicated by Adam, et al. that analyzing the relationship between ease of use, usefulness and usage of information technology is tricky. This was because the use of the systems was frequently required and was based on the job responsibilities of individuals (Adams, et al., 1992). In this study, the use of the data management systems included is not generally required. The investigation will point out whether the individual has been required to use these systems or not. It may be the only alternative for getting the information needed to perform ones job responsibilities, if the system is not required. As a result, this factor may require further study. The information access layer is defined as the component of the data warehouse that allows the user to access the data (Chen Frolick, 2000). To make the data available to the end-user in an easy fashion is the main goal of the information access layer. Most of the information access layers use graphic user interface (GUI) applications to run on the desktop computer (Chen Frolick, 2000). The factors that show the impact on the success of a data warehouse are flexibility and scope of the tools offered to users (Chenoweth, Corral Demirkan, 2006). It was recognized by Chenoweth, et al. that it is not easy to provide simple tools as well as ad hoc queries and reports (Chenoweth, et al., 2006). An investigation done by Murtaza indicates that the business client should be the one who drives the implementation process. His investigation further indicates that the organization will not receive the full benefit of the data warehouse until and unless the business user can easily plot a route and fully understand the detailed, summarized and historic data in the warehouse (Murtaza, 1998). The study given by Murtaza indicates that selection of a tool for evaluating the data management system should be reliable and constant with the sophistication of the user (Murtaza, 1998). Therefore, the study concludes that it seems proper for the data management system to have more than one access tool. The three tools that can be used to access data warehouse are: Standard Reports: The extremely protective option for accessing the data management system diminishes the complexity and vagueness (Chenoweth, et al., 2006). The first option for getting the information of data warehouse is to set the users and to develop and deploy a set of standard reports. Generally, this option is used for making executive decision. An executive report is provided with an easy access to a dashboard of metrics for reviewing on a daily, weekly or monthly basis. This dashboard might include enrollment management metrics in a university setting; for example, graduation rates over time, external data on department rankings, and tuition revenue trends. This option is generally used to offer information to a group of less-advanced customers. They have the need for the same set of standard information each day, week or month. Standard reports with parameter driven access: The second option is to provide a set of standard queries to the users. This gives the customers the power to select detailed parameters and also to select summary of detailed level data. The customers may look at enrollment trends for one particular department or division or may want to look at the numbers of faculties for one particular year provided by the department. Developing some standard reports and allowing the users to modify those reports by selecting only certain parameters can provide the customers with access to significant amounts of data without writing personalized reports. Ad hoc access: Ad hoc access query tool allows users to select the tables and data from the fields they wish to select. To meet the customers data need, users may simply get a flat file of data that can be allowed to analyze the own data in numerous ways. For instance, customers could obtain a flat file of overheads data. The customer can produce their own reports by furnishing it, by other sources, by department, by functional expenditure or by combining them all. The ad hoc query tool might also permit the customers to set their own preferences of reporting. It has also been beneficial to provide less restrictive access to some data management system users (Chenoweth, et al., 2006). It was founded by Clark that there will be an impact of the use and success of the system (Clark, et al., 2007). According to Clark, near about 20% users are the information producers and near about 80 % of users are information consumers (Clark, et al., 2007). The users who submit ad hoc queries that are used to create reports and analyses are termed as the information producers whereas the information consumers use the reports and information that is produced by the information producers. More powerful tools for accessing the data are required by the information producers. Analysis and Discussion Success Factor of Data Warehouse Earlier, the successful implementation process of an information system project was based on two factors management support and users involvement. A study conducted by Chenoweth, et al. also indicated that the comprehended availability of expert support, which could be a team of data warehouse or user experts or super user of data warehouse system, results a successful implementation of data warehouse system (Chenoweth, et al., 2006). In order to understand the purpose of data warehouse system, this support is very essential so that the user could use this system in an easy manner (Chenoweth, et al., 2006). The super users can utilize this system as a method for distributing their knowledge and awareness throughout the whole organization. According to the literature of Watson, it is very difficult to quantify the various benefits of a data warehouse because some of the benefits are intangible and the research has not been consistent in agreeing on what benefits should be measured and how to quantify them (Watson, et al., 2002). Some of the benefits related to the sample include: data accuracy, ease of use, customer satisfaction and useful information. Apart from this, it also includes decision confidence, system usage, time to make a decision and reliable information. Few of these measures will be incorporated in this studys questionnaire. Management and Executive Support: A factor that has been established long before is Management and executive support, which has led to the proper use of a management support system and success (Clark, et al., 2007). The executives play a vital role in laying down the resources so as to construct and support the systems. Apart from this, they will provide the drift to the proper use of the systems (Clark, et al., 2007). In addition to this, the management also understands that they should construct systems so as to collect and provide access to huge quantities of data. This process will help in the data mining and also assist in the decision making in the organization (Clark, et al., 2007). User Involvement: The main reason behind the development of the system should be the needs of the users. However, in those times, Alter found that participation of the user was not widespread in the projects related to the system development. His study reveals the cause of the low involvement of the user, generally stanching from the fact that systems might be sold and forced upon the users. Therefore, in each situation, the involvement level of user will show natural variation in every situation. Alter also describes that a relationship exists between the success rates implementation and user involvement. In 2007, a study carried by Clark et al. pointed the significance of user involvement in the growth of an analytic aid (decision). Because of the following reasons, involvement of users was regarded important (1) It helped in the development of the dedication and better understanding, which was required for successfully implementing the decision support tools and (2) It helped in tailoring the system as per the needs and requirement of the users and also depending on their role inside the organization (Clark, et al., 2007). The involvement of the user permits the system designer in better understanding of the users needs and broader goals of the organization. It also provides the designer with an opportunity to know the tasks required in achieving the desired goals. The understanding so developed is helpful in developing the ability of the designer so as to implement and built an efficient system. The fact that the user involvement is important in the development of the information system is not favored by all studies. In the study of Barki Hartwick, it was found that participation and involvement of users should be measured in a separate manners. According to them, users participation could be defined as the activities of users during the development of system whereas user involvement could be defined as a subjective psychological state that a user feels about the importance and relevance of the system (Barki Hartwick, 1994). The participation of the user can be direct participation, when he is participating directly in the process and it can be an indirect participation when a representative of the user participates on his behalf (Barki Hartwick, 1994). The participation is formal when it takes place through meetings, groups and some other mechanism while an informal discussion is done through informal relationships and discussions (Barki Hartwick, 1994). The participation can also vary in scope during the various stages of the process; that is, the participation may be in identifying the problem, evaluating the problem, formulating a solution, or implementing the solution (Barki Hartwick, 1992). Data Warehouse Implementation Though sufficient tools are available for each process involved in the design and development of warehouse, the subject is complex and requires participation of senior management and IS personnel. In practice, Data Warehouse conceptual model could be for the enterprise as a whole; however, it needs to be developed in stages to ensure its success and business benefits. So the implementation of full data warehouse would be in stages, starting with warehouse initiation project. This is done through segmenting the Data Warehouse in smaller components. This means defining high level enterprises model and enterprise data. The subset should have its own clear source options and business data, which it would create. This data must have business information value for strategic application. The subset could be visualized as critical management application, affecting key areas and so on. The steps involved in stage implementation are following: Establishing infrastructure namely DBMS, extraction, replication tools and report writers. Model that enterprise data from logical structure to physical structure. Prioritize the business data need and segment the enterprises data model matching to this need. Determine sources of data from internal system and applications which need to be handled as stated earlier. Simultaneously, collect the metadata about the data being considered for processing in Data Warehouse. Model the business data at both logical and physical levels. Finalize and implement security aspects and release the security code to the end users on the installation of Data warehouse. To get a better start on the project; it is better to initiate a preparatory project to get everybody in the organization to understand the why and how of Data Warehouse. Following activities are carried out for this purpose: Obtain necessary management approval to undertake such project. Initial exploration and education on data warehouse for the key people in the organization, i.e. key decision makers and key end users. Build a small Data Warehouse pilot: Present the same to the concerned people to justify and convince the need of it. Obtain the approval for building enterprises Data warehouse. Go for Data warehouse requirement definitions: This essentially means studying existing business strategies and business scenario. Looking for changing needs of strategies, the managers and decisions makers holding key positions in critical business functions should be able to envisage what their business data needs are to cast new strategies. Having ascertained the business data needs with enterprises wide data access, next step is to go for high level enterprise data model. Obtain the approval for enterprises wide data model, which will form the basis of designing Data Warehouse. This approval could be obtained by presenting the case for enterprises data model and its benefits. Prepare a road map to build the Data Warehouse with stages to obtain the benefits as it gets implemented. In this road map, following topics should be dealt with: Executive summary on business needs of Data Warehouse Note on business strategy, current and future Data Warehouse architecture. Explain three layer architecture (Operational Data, Reconciled Data and Derived Data). Inputs required and implications on existing information system, operational and functional. Potential areas of benefit and cost estimates considering hardware, software and tools. Data Warehouse design, development and implementation schedule. Project team approval by the management. Communication directive from the management to go ahead on the project. Launch the project The critical success factors for successful conclusion of Data Warehouse project are the same as that for any information system project. It requires long term commitment and involvement of key business managers whose business data needs will be served through Data Warehouse. A programmatic and stage implementation plan ensuring the success and assuring the benefits is necessary. The sound understanding of existing information system supplying operational data for data warehouse is necessary. The architects and developers must have mastery on related technology and tools for their effective application in building the Data Warehouse. Training the end-users for using data warehouse for fulfilling their business information needs and expectations is absolutely necessary. The point is that Data Warehouse makes them self reliant to meet their needs. They are not dependent any more on IS department to process their information needs. This is a cultural change. Hence, training in tools lik e report writers, spread sheets and SQL is necessary to exploit the benefits of Data Warehouse. CHAPTER 5 Conclusion In this research, I have analyzed different articles and found that Data Warehouse system is an important tool for the organization at the time of decision-making process. I have come to know the importance of Data Warehousing in various business ventures and institutions. The reasons behind the development and growth of Data Warehousing are the changes in the technology, changes in global economy and the innovations. If the previous task is completed successfully, the satisfaction level of the users can also be evaluated. There are two basic reasons for users not using the data warehouse systems; either the users were simply unaware of the existence of the warehouse or the warehouse was not perceived as helpful in completing their job responsibilities. According to my research analysis, there are more than 90% recipients, who are satisfied with the Data Warehouse systems and its techniques. They really feel that this system is very helpful to analyze information to take decisions within minimum time period. Different tools of data warehouse discussed in the report have the ability to run standard reports, select parameters for those standard reports, and provide data through ad hoc queries. In order to conduct a research in the future, it is essential for the researcher to analyze each and every aspect of the problem again because of the changes in the environment, technology, procedure, etc. So, it will be easy for him to conduct an appropriate research and giving a result which would be based on the accuracy and authenticity. References Adams, D., Nelson, R., Todd, P. (1992, June). Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication. Journal of Management Information System Quarterly, 16(2): 227-247. Barki, H., Hartwick, J. (1994, March). Measuring user participation, user involvement, and user attitude. Journal of Management Information System Quarterly, 18(1): 59. Benander, A. Benander, B. (2000). Data Warehouse Administration and Management, Information Systems Management, 17(1):71-80. Chen, L., Frolick, M. (2000). Web-Based Data Warehousing. Information Systems Management, 17(2): 80. Chenoweth, T. Corral, K., Demirkan, H. (2006, January). Seven Key Interventions for Data Warehouse Success, Communications of the ACM 49(1): 114-119. Clark, J., Jones, M., Armstrong, C. (2007, September). The Dynamic Structure of Management Support Systems: Theory Development, Research Focus, and Direction. MIS Quarterly, 31(3): 579-615 Coskun, S., Pohlen, T., Bozovic, N. (2002, Winter). A Review of Data Mining Techniques as They Apply to Marketing: Generating Strategic Information to Develop Market Segments. Marketing Review 3(2): 211 228. Foshay, N., Mukherjee, A., Taylor, A. (2007, November). Does Data Warehouse End-User Metadata Add Value? Communications of the ACM, 50(11): 70-77. Hsieh, C., Lin, B. (2002, December). Web-Based Data Warehousing: Current Status and Perspective. Journal of Computer Information Systems, 43(2): 1. Jawadekar, W. S. (2005). Management Information System (3rd Revised Edition). New Delhi: Tata McGraw Hill Publishers. Kothari, C.R. (2005). Research Methodology (3rd Edition). Delhi: New Age International (P) Ltd., Publishers. Marakas, G. M. (2003). Decision Support Systems (2nd ed.). Upper Saddle River, NJ: Prentice Hall. Murtaza, A. (1998). A Framework for Developing Enterprise Data Warehouses. Information Systems Management, 15(4): 21 27. Pipe, P., (1997, October). The Data Mart: A New Approach to Data Warehousing, International Review of Law, Computers Technology, 11(2): 251-262. Rahman, N. (2007, Spring). Refreshing Data Warehouses with Near Real-Time Updates. Journal of Computer Information Systems 47(3): 71 80. Sen, A., Sinha, A. (2005, March). A Comparison of Data Warehousing Methodologies. Communications of the ACM, 48(3): 79-84. Watson, H., Goodhue, D., Wixom, B. (2002, May). The Benefits of Data Warehousing: Why Some Organizations Realize Exceptional Payoffs. Information Management, 39(6): 491. Wixom, B., Watson, H. (2001, March). An Empirical Investigation of the Factors Affecting Data Warehousing Success. MIS Quarterly, 25(1): 17-41.

In French, Ever Hear of a Pépère

Pà ©pà ¨re, pronounced  pay pehr, exists as both a noun and as an adjective with distinct, but related meanings. In all its meanings and usages, it is an informal term. Examples of use and some expressions are included in each section. Pà ©pà ¨re: Noun Pà ©pà ¨res perhaps most frequent use  is akin to baby talk—the affectionate name small children give to their grandfather: grandad or grandpa, gramps, as in: Salut  pà ©pà ¨re  ! Hi grandad! Pà ©pà ¨re  said by an adult can refer to: a man or boy who is fat and calm (un homme ou garà §on gros et calme), as  many grandfathers are  or (pejoratively) an old-timer  Ã‚   Pà ©pà ©Ã‚  or  grand-pà ¨re:  What a young child  calls an old grandfather (un vieux pà ©pà ¨re), as in: Pà ©pà ©, donne-moi mes jeux, sil te plaà ®t.   Grandpa, give me  mes toys please.   Gros Pà ©pà ¨re: Noun An informal expression for a cute child or a cute animal baby, as in: Tiens, le  gros pà ©pà ¨re  ! Look at the cute little baby! When referring to a man, it means: tubby (with affection)fat slob (with derision) Pà ©pà ¨re: Adjective When referring to an adult man, it means: quiet, calm, peaceful, nice and easy (as many grandfathers are)   When it refers to a thing, such a job or a life: quiet, easy, uneventful, cushy Un petit boulot pà ©pà ¨re   a cushy little job Quel boulot pà ©pà ¨re ! What a cushy job! Une petite vie pà ©pà ¨re   a cozy little life   On ne veut quune vie pà ©pà ¨re. All we want is a quiet life. Faire en Pà ©pà ¨re: Verb   agir tranquillement   to act calmly (as many grandfathers do)

Digital World Of The 21st Century - 1926 Words

In the digital world of the 21st century, eBooks have become yet another explosive trend in people’s lives across the world. Readers now have the option of choosing to read a printed book or to read an eBook off of an eReader, computer, or other device. Both printed books and eBooks have varying functions, features, and uses. Many studies also show that eBooks and printed books have a varying effect on the reader’s comprehension. As the book has evolved, we have also evolved into different readers, users, and learners. All readers need to take the time to understand the different features and functions of an eBook versus a printed book in order to understand the effect each has on our reading experience. There are many advantages of†¦show more content†¦You also have the ability to take notes, look up words on the integrated dictionary, and search on the internet directly from your eBook or eReader. You can also get free sample downloads before you buy an eBook—which saves you money and time. Another great thing about eBooks is that they are typically sold at a lower cost than printed books. On the other hand, as Abram mentions, there are many advantages of a printed book compared to an eBook or eReader. One of the most popular advantages of a printed book is the look, feel, and sensory experience you get with a physical book. You can touch it, flip the pages, write in the margins, and smell the book—something you can’t do with an eBook. Printed books are also easier to read than eBooks in situation where lighting can affect your eReader or device’s screen. The packaging, layout, and font tell the author’s story. Many times on an eBook, the format of the original book is skewed. Think about all the times you’ve been reading a printed book and the suspenseful sentence ends right at the end of the page. You have to quickly flip the page to find the answers you need. On an eBook, many times the original alignment that the author wanted won’t work out because of the size of the font or pages, thus you don’t get the same experience as a printed book. Printed books also have page numbers, where eBooks have percentages or page numbers that go into the

Computer Information System Decision Support †Free Samples

Question: Describe about the Computer Information System for Decision Support System. Answer: Introduction Information management system is important for any business improvement system and operational management (Ward Peppard, 2016). ERP or enterprise resource planning are very important for integration of the business system. ERP technology and software are classified into industry specific ERP, Web based or cloud service ERP, small business ERP, and computer exchange ERP solutions (Leon, 2014). The strategies are developed for the improvement of the security function in the business organization. In this assignment the various types of ERP models are being analyzed for understanding their impact on the business operations. The assignment consists of taxonomy of the ERP model for understanding the comparison between the outdated information system and the advanced information system. Various examples for ERP software are shown in the assignment and it would help in understanding the extent of the technological development in information system management. The suggestion provided at the last part of the report would be helpful in providing the effective ways for securing the information system for any business organization. Classification of different types of ERP software There are various types of enterprise resource planning software used in integration of the business system. They are classified into industry specific ERP, Web based or cloud service ERP, small business ERP, and computer exchange ERP solutions (Monk Wagner, 2012). Industry specific ERP: the Infor ERP is a ERP solution that offers the solution for manufacturing and distributing process of the industries (Nettstrater et al., 2015). The software solution has supported over seventy five thousand businesses across two hundred countries. The industry specific ERP are used by large scale business entities as they need customized operations for their business needs. Web based or cloud service ERP: The advanced ERP system are broadly sued by many companies. However, there are some companies who use the web based software solution for the integration of the business activities. The cloud based server for business integration has been termed as SaaS or software as a Service. The cloud service ERP helps in accessing and storing the data over the internet based storage system. It would help in remote access of information and data. The cloud ERP provides the organization with fast and accurate access to the information system. Hence, it is ideal for all scales of businesses. However, it is best suited for small business models. Small business ERP system: this type of ERP system is helpful for small operations like sales and order management (Nettstrater et al., 2015). The human resources management does not require large data house for small scale business organizations. Hence a lower scaled ERP system is beneficial for providing functionality to small scale business problems. It can be implemented at cheaper cost and is very ideal. Computer exchange ERP solutions: Computer exchange ERP solutions are useful for helping the business centers in improving the efficiency of the operations (Chang et al., 2013). The outdated ERP are not liable for providing the required functionality to the business management. The upscale and updated ERP system would help in increasing the opportunities for accelerating the growth of business. Some examples of different ERP software are mentioned below. Software name Features SAP R/3 Used in over 120 countries, over 90000 customers, the services are good and excellent support SAP B1 Business one, suitable for SMEs, low cost, 15 core modules, and effective localization of SAP B1 LN/BaaN Project based discrete operations, increases productivity, efficiency improvement, and reduction in costs Microsoft Axapta or Dynamics AX 2009 Used for mid-sized business operations, improve productivity, used by wholesale distributors, service companies, and retailers Microsoft Navision or dynamics NAV Assist in financing, manufacturing, SCM, CRM, and analytics JD Edward enterprise one Integrated applications, standard based technology, and low total cost Oracle Suite Financials for E business Pre integrated financial processes, dynamic budgeting, forecasting and profit analysis Oracle people soft enterprise Suitable for complex businesses, improving the performance of the operations, seamless internet services, large choices of infrastructure, and heterogeneous applications Table1: Different examples of ERP software (Source: Chang et al., 2013, pp.-1461) Comparison of legacy computer system and information security architecture Comparing legacy computer system of Apple and Microsoft Comparison heading Apple Microsoft OS Mac short form for Macintosh It refers to the computer operating system created and patented by Apple INC. Different versions of Windows like windows vista, windows 8, and windows 10. The IBM based operating systems has been termed as Personal computer or PC (Arthur, 2014). Cost Computers of Apple costing start from $500 or above. Mac mini costs around $550, Mac Air notebook costs around $900, and IMac costs around $1100 (Arthur, 2014) Windows and its peripherals are cheaper in compare to the Apple computers. Desktop PCs are almost 40% cheaper than Mac. Manufacturers Apple Hewlett Packard, Dell, Asus, Lenovo, and Acer Developer Apple Microsoft, Ubuntu, and Sun User Home and Business users (core and technical department) Business and home users Compatibility Can operate all types of software files Mac based files are not supported Market reach App developers, graphic designers, and music producers Writers, students and for general users Piracy No need of activation Unique activation key is provided Registry No Yes Table2: Comparing legacy computer system of Apple and Microsoft (Source: Wonglimpiyarat, 2012, pp.-101) Comparing information security architecture of Apple and Microsoft Information security architecture of Apple The apple devices are the most secured device that is being used currently. The software consists of data protection class within the layers of app sandbox, user partition, OS partition and file system (Wonglimpiyarat, 2012). The hardware is protected by using kernel that consists of secure enclave and element. The Crypto engine and root certificates of apple are also used for protecting the device from any security issue. Information security architecture of Microsoft The information security used in Microsoft is based on the advent of threat modeling. Threat modeling is an analysis of the risk factors and threats for information security. The four core elements of threat model are processes, data stores, data flow and external entities. The security network architecture of information in Microsoft are protected from Spoofing(S), Tampering(T), Repudiation(R), information disclosure(I), denial of service(D), and elevation of privilege(E). Its acronym is STRIDE (Wonglimpiyarat, 2012). IPSec or transport security layer is used for authentication of the device. The field gateway is protected by using TLS RSA or PSK, RFC 4279, and IPSec protocols. Table3: Information security architecture of Apple and Microsoft (Source: Stewart, 2015, pp.-29) Developing the taxonomy of ERP architecture The taxonomy of ERP architecture shows five basic elements for the information management system (Ali Cullinane, 2014). They are Management (Top Level), Strategic level, Tactical level, Operational level, and Integration and Realization. Management (Top Level): It consists of Business class, Change management, Project management, and Training (Islam Nofal Yusof, 2016). The management is the top most level of the ERP architecture and it is responsible for all the operations in the business organization. The communication process in the ERP system is very important as it holds all the operations of the organization together. Strategic level: It consists of Implementation process, Hiring procedure, Benchmarking activities, and Evaluation of the outdated process. Tactical level: It consists of Client consulting activity, Software selection process, and implementing approach for the information system. Operational level: It consists of Business process, Configuration of the information system, finalizing the activities, and Going live that means implementing the information system (Islam Nofal Yusof, 2016). Integration and Realization: In this step the ERP architecture is implemented and the outcomes from the system are realized for the business organization. The taxonomy of ERP architecture implementation for improving the legacy system can be understood from the provided figure. Figure 1: Taxonomy of ERP architecture implementation system (Source: Roh Hong, 2015, pp.-636) Suggestion for improving the information security system The strategies that can be used for improving the information security and management in the organization are policy development, education and training, enforcement of the security model, information exchange, and co-operation (Peltier, 2013). Policy development: The organization must encourage and adopt the appropriate laws, policies, rules, and agreements for information security management (Gray, Miller Noakes, 2013). It would help in harmonizing the technical standards among the whole world. The promotion of the expertise would be greatly influenced by the formation of policy for information system. Education and training: it would help in promoting the necessity of the information and security of the information stored over the database (Sacks Pikas, 2013). The organization would have to make sure they have educated an trained them about the importance of the information system and its security. Enforcement of the security policies: it would require providing access to the implementation of the policies recognized for information security improvement (Gray, Miller Noakes, 2013). The organization would need to expertise and exercise ways for implementing security of the information system. Information exchange: the information storage system must be made secured and the process of transferring must be made explicitly (Sacks Pikas, 2013). The exchange of information must be related to the guidelines of the policies and their implementation in the information system management. Co-operation: the security of the information system can be implemented by the co-operation of the employees (Peltier, 2013). The mutual understanding for the information security is necessary for any organization. Conclusion Information management system had held an important place for any business improvement system and operational management. Different types of the ERP are industry specific ERP, Web based or cloud service ERP, small business ERP, and computer exchange ERP solutions. The strategies that have been developed for the improvement of the security function in the business organization would help in understanding the information system management and it security features. The Policy development, Education and training, Enforcement of the security policies, Information exchange, and Co-operation are necessary for improving the security of the information system management. In this assignment the various types of ERP software had been classified for developing the scope for improving the information system models in the business organization. The assignment had shown the extent of ERP model and its structure for information system management. 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