System analysis and design Essay Example | Topics and Well Written Essays - 250 words

System analysis and design - Essay Example Universities have been offering the courses to meet the increasing demand for professionals in data analysis. North Carolina State University that has been offering a similar course since it launched of the advanced degree program in analytics in 2007. In addition, the school is also expanding to meet the demand. Other universities too plan on launching the degree course. An example is the McCombs School of Business at the University of Texas that plans on launching a master of science in business analytics program in the fall. There is also a growing interest in acquiring knowledge required in handling data as shown by the large number of people seeking enrolment in such programs. As the analysis above indicates, higher learning institutions have found it necessary to provide advanced degree courses in analytics to fill in the gap in society. There is a growing need to educate the society about the emerging trends in system analysis. In a rapidly changing information technology sector, a systems analyst must strive for professional improvement (Shelly and Rosenblatt 30). There is ongoing effort by universities and colleges to provide advanced courses in design to ensure that they fill up the gap that has been brought up by the demand for employees with skills and advanced training in analytics. Statistics, from North Carolina State University, indicate there are readily available and well-paying jobs available for those who graduate with big-data

Semantic Web and Implications Essay Example | Topics and Well Written Essays - 1000 words

Semantic Web and Implications - Essay Example This paper stresses that you would also like to know how long the respective shops are open that day, hence, you start surfing the various websites of dealers and compile gathered information in a list. Although, the websites of the various dealers are designed very differently, it is still easy to gain information such as at the opening times of a branch. Gathering the list is a bit cumbersome, but an intellectually easy task to be accomplished. It is difficult to automatically retrieve content from various web shops, such as information like sales price are all formatted differently and embedded in different places. The Semantic Web helps to unify this complicated data in the background, without changing the layout. According to the discussion Semantic Web Semantic Web is the extension of current web which is better at enabling the computers and individuals to work in cooperation. User locates the information on the internet with the help of two main tools, search engines and catalogues. Catalogues were designed by humans who were accurate in terms of results but search engines were designed to elsewhere. Search engine skims the internet websites and searches for changed pages and mechanisms of indexing. The catalogues store the information on the basis of the usage of the words. The inability to comprehend the words and identify the relationship while searching for query is the drawback identified in search engines due to which semantic web is taking place. Anyone who enters the phrase sequence "Sales for Siemens in Germany in 2005" into a search engine receives all possible outcomes. However, no accurate answers are ever retrieved. Be it Altavista, Yahoo or Google - no search engine today is a ble to "understand" such a query. Search robots react to hidden tags on websites called metadata. If they do not properly classify it comes to "irrelevant results" or to a "too large outcome space†. Dissatisfied users complain about search engines, according to market research firm Jupiter Research, "Dr. Know", the all-knowing oracle of Steven Spielberg's "AI (Artificial Intelligence)", today's world of search is still far away. In the science fiction film, the protagonists asked a question, and if "Dr. Know" did not have an answer right, they simply asked again and marginalized by the context of the question further and further. Semantic technologies allowed computers to process the content of music, images and videos in a better way. Semantically means that content does not only have a meaning, but is also related to other meanings, thus forming hierarchical classes. Future of Semantic Web and Challenges The concept is regarded as an impractical concept presented by the Web Specialists.  

What has been the impact on money supply in the U.S. of the recent Essay

What has been the impact on money supply in the U.S. of the recent mortgage crisis - Essay Example In America over the preceding few years, loads of home buyers had procured costly houses with out of the line mortgage products funded by unrelenting mortgage lenders. The incidents have wrecked the liaison between money supply growth and the recital of the US financial system. The current deceleration in housing trade, inferior house costs and the retuning of mortgage variable rates has initiated a downturn in the mortgage sector. The predicaments are principally manifested in the "sub-prime" sector and are imitated in swiftly growing delinquency, non-payment and foreclosure rates. This paper hereby briefly analyzes the impacts of current US mortgage crisis on money supply.It is an undeniable fact that Money Supply has an influential effect on economical commotions. Amplification in money supply inspires improved expenditure as it places added money in the hands of customers making them to feel richer and eventually inspiring them to swell their expenses causing temporary boost in financial activities and controlling deflation. (Handa, 2008) The phase of 2003-2006 witnessed exceptionally near to the ground interest rates along with consumer hopes of increase in double-digit house costs, assisted a record $3.2 trillion in house mortgages being written by lenders, with approximately 20% of this sum contribution towards subprime. The subprime mortgage sector also served supplicants having bad credit history at elevated interest rates. (Handa, 2008) It is now well known that in array to boost their profits, banks issued huge loans to investors engaged in US housing markets, but owing to sudden price decrease in housing sector, the quantity of loan defaulters increased causing liquidity crunch for banking institutions creating an environment of money crunch for the markets based on investor and end-user relations and eventually led the international markets to face mortgage crisis. (Ashdown, 2002) The mortgage crisis led countries to increase the money supply to control the sudden swell in economic inflation and increased interest rates. Faced with the slither in the actual economy and the crisis in the financial system, the Federal Reserve implemented extraordinary moves i.e. a $200 billion loan package was issued to stanch money constrictions. (Axilrod, 2009) In 2008, the majority of US money supply augmented noticeably as the governmental authorities interceded to infuse money into the system. Traditionally, an impulsive boost in the money supply resulted in a raise in interest rates to deflect price increases or inflationary prospects. (Ashdown, 2002) Source: New York fed The US government, up to now had issued huge amount of currency to assist procuring of lethal mortgage-backed securities and other badly performing resources from banks owing to the anticipated risk of price increases and dollar depression. Though, this risk is of a reduced amount of worry to the Fed as compare to the depression and languish growth as in 2008. Owing to the black economical month of March, 2007 in which over 25 subprime lenders declared insolvency, large losses or setting themselves up for sale, several lenders discontinue home equity as well as "stated income" loans. To control the total collapse of mortgage industry in July, 2007 Federal Reserve increased money supply by approximately $100 billion to facilitate retail financial institutions with credits at lower rate following with another $41 billion during late Oct - Nov, 2007 which was the biggest lone increase by the Federal Reserve since Sept 19, 2001 i.e. $50.35 billion. (Barth, 2009) In accordance with the review of literature provided by several economists, it is revealed that Money Supply is not dependable on the quantity of currency printed but it depends on the pace of flow i.e. "how many times it changes hand." (Mishkin, 2008) The trouble is that the rate of circulation had felled

Strategic finance essay with word counts no less than 1500

Strategic finance with word counts no less than 1500 - Essay Example Like any other capital budgeting model, CAPM has its own weaknesses and strengths. In order to improve its usefulness, the standard capital asset pricing model has undergone various developments and modifications in the recent past. Since its conception about four decades ago, the Capital Asset Pricing Model has been used widely in applications to estimate cost of capital of firms and evaluate the performance of asset portfolios in companies. This report argues that CAPM has received such a wide support and use in the industry despite its strong assumptions because it provides powerful and reliable predictions about risk measurements and the relationship between risk and expected return. CAPM has several problems which are considered by many as the results of theoretical failures emanating from the strong assumptions of the model (Rubinstein 2006). However, they could also be caused by the difficulties of its empirical implementation. Although these problems are common, it is also understood that other models have their problems too. Therefore, the best model is the one which has proved to be successful in its application. Capital Asset Pricing Model is the model with such wide and successful application becaus e it provides powerful and reliable predictions about risk and returns of a given portfolio of assets. The Capital Assets Pricing Model (CAPM) suggests that the equilibrium rates of return of risky assets in the market have a linear relationship with the market portfolio. CAPM is used to establish a theoretical value of required rate of return of an asset in a diversified portfolio. This takes into consideration the systematic and market risks which are non-diversifiable risks (Rubinstein 2006). The model also considers the markets expected return and the theoretical risk-free assets expected return. CAPM draws from the portfolio theory developed by Harry Markowitz (1959). The formula of calculating expected return of an asset portfolio