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Management Information System

Jun 16, 2015

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  • 1. 1 Artificial Intelligence It is the study of how to make computers do things which, at the moment, people do better. In other words, it can be defined as the study of making of computer with the ability to mimic or duplicate the human brain functions(Model, 2012). John McCarthy coined the term in 1956, at Massachusetts Institute of Technology, defines it as "the science and engineering of making intelligent machines(Gaurav, 2013). Researchers are creating systems which can mimic human thought, understand speech, beat the best human chess player, and countless other feats never before possible. History of Artificial Intelligence Evidence of Artificial Intelligence folklore can be traced back to ancient Egypt, but with the development of the electronic computer in 1941, the technology finally became available to create machine intelligence. The term artificial intelligence was first coined in 1956, at the Dartmouth conference, and since then Artificial Intelligence has expanded because of the theories and principles developed by its dedicated researchers. Through its short modern history, advancement in the fields of AI have been slower than first estimated, progress continues to be made. From its birth 4 decades ago, there have been a variety of AI programs, and they have impacted other technological advancements. Thinking machines and artificial beings appear in Greek myths, such as Talos of Crete, the golden robots of Hephaestus and Pygmalion'sGalatea. Human likenesses believed to have intelligence were built in every major civilization: animated statues were worshipped in Egypt and Greeceand humanoid automatons were built by Yan Shi, Hero of Alexandria, Al-Jazariand Wolfgang von Kempelen. It was also widely believed that artificial beings had been created by Jbir ibn Hayyn,Judah Loewand Paracelsus.By the 19th and 20th centuries, artificial beings had become a common feature in fiction, as in Mary Shelley's Frankenstein or Karelapek'sR.U.R. (Rossum's Universal Robots).Pamela McCorduck argues that all of these are examples of an ancient urge, as she describes it, "to forge the gods. Stories of these creatures and their fates discuss many of the same hopes, fears and ethical concerns that are presented by artificial intelligence.

2. 2 Mechanical or "formal" reasoning has been developed by philosophers and mathematicians since antiquity. The study of logic led directly to the invention of the programmable digital electronic computer, based on the work of mathematicianAlan Turing and others. Turing's theory of computation suggested that a machine, by shuffling symbols as simple as "0" and "1", could simulate any conceivable act of mathematical deduction.[23] This, along with recent discoveries in neurology, information theory and cybernetics, inspired a small group of researchers to begin to seriously consider the possibility of building an electronic brain.[24] The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956.The attendees, including John McCarthy, Marvin Minsky, Allen Newell and Herbert Simon, became the leaders of AI research for many decades.They and their students wrote programs that were, to most people, simply astonishing: computers were solving word problems in algebra, proving logical theorems and speaking English. By the middle of the 1960s, research in the U.S. was heavily funded by the Department of Defense and laboratories had been established around the world.AI's founders were profoundly optimistic about the future of the new field: Herbert Simon predicted that "machines will be capable, within twenty years, of doing any work a man can do" and Marvin Minsky agreed, writing that "within a generation ... the problem of creating 'artificial intelligence' will substantially be solved". They had failed to recognize the difficulty of some of the problems they faced.In 1974, in response to the criticism of England's Sir James Lighthill and ongoing pressure from Congress to fund more productive projects, the U.S. and British governments cut off all undirected, exploratory research in AI. The next few years, when funding for projects was hard to find, would later be called an "AI winter" Fields of Artificial Intelligence: Games playing: programming computers to play games such as chess and checkers Expert systems: programming computers to make decisions in real-life situations (for example, some expert systems help doctors diagnose diseases based on symptoms) Natural language: programming computers to understand natural human languages 3. 3 Neural networks: Systems that simulate intelligence by attempting to reproduce the types of physical connections that occur in animal brains Robotics: programming computers to see and hear and react to other sensory stimuli(L, 1999) Business Intelligence Business intelligence (BI) is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information. It allows business users to make informed business decisions with real time data that can put a company ahead of its competitors. Traditionally, core features like reporting and analytics have been the focus of BI technology choices, but as those features get commoditized, a whole new set of possibilities has emerged. Forrester's BI research shows that the technology is evolving and that enterprises on the cutting edge of these new trends can gain competitive advantage in their industries. SOURCE http://www.forrester.com/rb/Research/topic_overview_business_intelligence/q/id/39218/t/2 Business Intelligence components In most cases Business Intelligence involves the use of multidimensional analysis and reporting. By providing multidimensional analysis and reporting the company often builds a Company Data Warehouse to assemble the needed data. However the term Business Intelligence covers at least the following five components that will be explained in more detail in the following: 1. Multidimensional analysis 2. Reporting 3. Data mining 4, Financial consolidation and budgeting 4. 4 1, Multidimensional analysis This area covers the possibility to slice-and-dice data (factual information) in many dimensions. For many this is known at pivoting data. A pivot table is something that you can build and use in most spreadsheets including Excel. In Excel you can summarize data in a pivot table on many levels on each dimension and you can have a table of rows and columns of summarized data in both dimensions as well as filtering the shown data. Dimensions are often a hierarchy with multiple levels (product groups down to product level eg.) From a more technical perspective most database suppliers and Business Intelligence suppliers support multidimensional analysis with a special multidimensional database. A multidimensional database is often also called a CUBE. 2, Reporting Most companies have a need for different type of reports. In many cases hundreds of different type of reports and occasionally often more. Business Intelligence software often has comprehensive reporting tools available that can extract and present data in many different media types (like over an internal Web page/Intra net, Internet (to customers), Excel file format, PDF format e.g. In many cases these reporting facilities will be controlled by parameters that can be chosen real time and present a report that has been run directly against data (often a Data Warehouse or multidimensional data). 3, Data mining Data mining, a branch of computer science, is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. Source:http://en.wikipedia.org/wiki/Data_mining In many cases Business Intelligence also covers some functionality to perform Data Mining on the company data. As the definition describes above the purpose is to find (so far unknown) patterns from large data sets. 5. 5 In general to use the methods to find some new information in regards of already collected data and with this new information of patterns to be able to make informed business decisions 4 Financial consolidations and budgeting In many cases the Business Intelligence area also covers systems and functionality for Groups to perform financial group consolidation and budgeting. This area covers the whole aspect of elimination of intercompany transactions within a group to present the financial figures as these intercompany transactions had never happened and that the group is presented as one entity. In some cases this area within consulting companies also covers some elements of Performance Management and metrics like Key Performance Indicators BI converts data into useful information and, through human analysis, into knowledge. Some of the tasks performed by BI are(S.Negash, 2004): Creating forecasts based on historical data, past and current performance, and estimates of the direction in which the future will go. What if analysis of the impacts of changes and alternative scenarios. Ad hoc access to the data to answer specific, non-routine questions. Strategic insight. Artificial neural networks One type of network sees the nodes as artificial neurons. These are called artificial neural networks (ANNs). Anartificialneuronisacomputationalmodelinspiredinthenaturalnens. When the signals received are strong enough (surpass a certain threshold), the neuron is activated and emits asignal though the axon. This signal might be sent to another synapse, and might activate other neurons. The complexity of real neurons is highly abstracted when modelling artificial neurons . These basically consist of inputs(likesynapses), which aremultiplied by weights(strengthof theirelectivesignals),and then computed byamathematical function which determines the 6. 6 activation of theneuron. Another function (which maybethe identity)computes the outputof the artifi