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Essays

Math anxiety is a common phenomenon; some may style it a disease that inflicts so many individuals from children upwards to adults. The ramifications of this impediment are most deleterious for individuals who have to study the subject in order to obtain passing, or excellent grades in it, in order to move on to further subjects and success. Academic researchers have proposed a variety of interventions each of which can be reducible to three categories: curricular strategies, instructional strategies, and non-instructional strategies. A running thread though most seems to be the need for the student to control her own direction. Preventing mathematical anxiety can liberate the brain from the learning disablement of procedural memory that only intensifies the cycle of mathematical failure. This essay discusses origin and strategies of math anxiety

The Shakespeare play King Lear has been adapted for modern audiences and staged at the University of Miami's Jerry Herman Ring Theatre. Lee Soroko was the director, and made the decision to apply a modern context to the…

Web 2.0 technologies are revolutionizing every aspect of marketing and this includes the marketing of a company to prospective employees as well. The intent of this paper is to show how Web 2.0 technologies can be used for gaining access to more qualified candidates, and helping to keep them interested in the company over the long-term.

On Valentine's Day in the year 2005, a group of already wealthy young computer geniuses began their brainstorming and introductory work on a videography platform for the Internet . Similarly to the origination point of…

Organizational Behavior Terminology and Concepts

Student finance aid can be described as funds given to the student to make it easy for them to fix cost of education such as fee and tuition, room and board, supplies and books where the students are undertaking their…

Dear Graduates, Today, as your professors, friends, and family members stand before you, we are looking at the future: a future that is filled with hope. You, sitting in your chairs, dressed in blue caps and gowns, are…

The level of uncertainty and risk that pervade many enterprises today is growing, as the dynamics and economics of markets are changing rapidly. The many rapid, turbulent structural changes in industries is also leading to a greater reliance on analytics and the nascent area of Big Data as well. The potential of this second area, Big Data, is in determining patterns in massive data sets that have in many cases been collected for decades within enterprises. The abundance of data within enterprises, when combined with Big Data aggregation and analytics techniques, can be used for drastically reducing risk and uncertainty in even the most challenging and fast-moving industries. Big Data is being hyped heavily by analytics systems and enterprise application providers as well, as this category of software allows for the use of long-standing analytics and business intelligence (BI) tools expanded supporting larger data sets. Many companies today are working to create enterprise-wide platforms for managing massive data sets, many of them integrating legacy and 3rd aprty databases many of which have never been integrated into a broader platform strategy before (Jacobs, 2009). These larger data sets and their inherent complexity make the overall analysis, aggregation, creation of taxonomies and customizing of reports challenging and difficult to achieve with the baseline or current set of analytics and BI tools available today however. The continual evolution of these applications and the fine-tuning of specific aggregation technologies including Hadoop and Map Reduce (Jacobs, 2009) have also contributed to making Big Data a more strategic foundation fro decision making. Enterprises are facing greater time and cost constraints than ever before, which also leads to the create and continually invest in larger data sets, analytics, BI and advanced reporting technologies all orchestrated to make the most of the terabytes of legacy data companies have (Chisholm, 2009). The rapid development of analytics, BI and data reporting platforms and tools has led to a level of innovation in enterprise software that is making it possible for enterprises to get more insights from the terabytes of data they have been collecting for decades. This category of software tools include analytics, BI, data visualization, product lifecycle data and predictive analytics all orchestrated to create a common platform for reducing risk while bringing greater intelligence into an organization (Ericson, 2010). As is the case with any high growth enterprise software category, there is an abundance of hype surrounding what these analytics and BI platforms and tools are and aren't capable of. The tendency to overlook the very difficult processes to extracting, transferring and loading (ETL) data from legacy systems and creating a highly effective ecosystem of data is very expensive for companies who have never attempted this before. Further, the methodologies needed for consistently and accurately capturing the data within a given enterprise require a level of discipline that many companies are lacking in their core process areas (Jacobs, 2009). Simply put, it is very hard work to capture all the heterogeneous sources of data throughout an enterprise, from the legacy systems to the 3rd party databases, and then perform ETL functions on them in order to create a new system of record for the entire organization to make use of (Ericson, 2010). Yet for organizations to capitalize on the potential that exists from these many diverse forms of information, intelligence and insight throughout their businesses, they must take the time and effort to create a unified, highly integrated single system of record to galvanize their Big Data strategies together (Jacobs, 2009). The objective of this analysis is to provide the arguments for and against having Big Data included in the strategic decision-making process within an enterprise. The strengths are presented first, followed by the weaknesses of this approach to harnessing data throughout an enterprise. The strengths and weaknesses are next compared and an assessment provided. One of the most prevalent technologies used for accomplishing Big Data analytics and intelligence are MapReduce and Hadoop, two aggregation technologies that can compress terabytes of data into taxonomies and quickly analyze them (Jacobs, 2009).

The concept of "goal translation" in the context of the STM case is critical to the success of the entire TQM initiative and strategy. The single most critical success factor for any TQM initiative is change management…

Biblical folklore has provided the foundation for many contentious arguments regarding its meaning and subsequent purpose. Many pundits and religious practitioners have varying views as to the underlying meaning of the occurrences within the bible. This debate has been waged for many centuries spawning various religious beliefs in its wake. The overall umbrella of Christianity has now fragmented into various systems, practices and beliefs. It is because of this fragmentation that honest and open debate has occurred. One such debate is centered on the story of Adam and Eve. Many practitioners of Christianity recall the creation of Adam and Eve subsequently followed by their exile. Many believe this exile to be a curse upon mankind, in which all civilization must bear. However, it is my contention that the exile from the garden of Eden was not a curse by rather an opportunity for mankind to flourish. As a result of this exile mankind was given the opportunity to create vast and wondrous civilizations. Society advanced in regards to their education and subsequent motivation. All of which occurred after the exile from the Garden of Eden