Three Approaches Applied to Business Intelligence - Essay Example

RUNNING HEAD: THREE APPROACHES APPLIED TO BUSINESS INTELLIGENCE.  Topic: Three Approaches Applied To Business Intelligence Name: Institution: Three Approaches Applied To Business Intelligence Introduction Business intelligence is being used in corporations to assist in decision making thus some time they are also referred to as decision support systems. Due to advancement of technology and increased need of managing data and information the task has increasingly being more complicated and time consuming to analyze data or operational scenario for decision making. Business intelligence refers to processes, applications, skills, practices and technologies which are used in a business environment to support indecision making. Use of Business intelligence systems ease analysis, increases reliability and improve on quality of deliverables. This research paper shall compare and contrast three approaches of business intelligence namely Standard statistical methods for quantitative data, Semantic analysis methods and Geographic Information in relation to their basic assumptions of the techniques on what they are, what they do and their uses. Standard statistical methods for quantitative data Standard statistical methods for quantitative data is used for decision making which is largely based on application of statistical data analysis which is used for probabilistic risk assessment of the decisions being done (Delorme, 2008). The methods used are usually parallel or follow improvement of other sectors, which have adhered to such measures and comprehensive results have been achieved, these is the trail which statistic method of quantitative data follow to develop. Better decision making under uncertainties motivates methods development. Under uncertainty decision making is mostly fostered by application of statistical analysis of data for probabilistic assessment of risk in ones decision. Executive need to have in mid two key standing block; one so to lead others to apply statistical thinking on daily basis, two for the purpose of continuous improvement concept application. This study helps one with directives approach that provide one with hands on experience that generates and promotes techniques and statistical knowledge of the application of this methods in making educated and wise decisions when business data is in variation. The study show cases statistical thinking through an approach that is data-oriented. The study methodology is needed for the accumulation of sound and timely answers that affect decision making in different business entities by the executives and managers. It provides the principals with knowledge of how to effectively and well educate how to enhance the use of data-oriented approach in the decision that is essential for the development purposes of the firm. The data described in this study is mostly in form of report and numbers as opposed to qualitative data analysis. The analysis here is used to bridge between executives or managers and task force. These helps the executives to best execute decision that are well balanced and hold proper educational analysis and method of how to execute them. It also provides the principals involved in decision making with knowledgeable concept of how to avoid pitfall along the terrain of statistical data variation methodologies. The data is used by managers to help evaluated problems that may arise before hand and how to best approach them, or how to counter attack crisis before they arise. Strength of qualitative method of data analysis is that this method analyzes and produces quantifiable, factual and reliable data usually comprehensive even over a large population. This kind of data analysis is often mostly appropriate for the conduct of needs assessing and for comparison evaluation of outcomes using base line data. This methodology has enough shares of its problems will enlist some major ones; these system breaks down when there is difficulty in measuring or quantifying of the phenomenon under study this gives the direct authority under this process head ache, it’s greatest and most weakest of the quantitative methodology is it de-contextualizes human in ways that extinct all events from true world setting thus ignoring variables effects that are not inclusive in the model Semantic analysis methods Semantic analysis method which is used in decision making is used to track function/variable/type checking and declaration. This method of analysis is done by use of computerized systems, which uses a complier to encounter declarations which are new and record the type of information which is assigned to the identifier. As the complier continues checking the rest of the program it usually verifies that the identifier type is represented in operations which are being performed. The parameters which are set on a function used by the program must match the arguments being used for both type and numbers used. The language used would require the identifiers to be unique such that they will forbid two global declarations from sharing the same name. The arithmetic operands being used must be numerical and there are possibilities that they might be the exact same type. However, some semantic analysis would be done at the middle of parsing. This arises when particular construct are recognized especially when additional expression the parser action would check both operands and verify on whether both of them are compatible for the operation being done and whether they are of numeric type. When performing semantic analysis there are set of type of values and operations which are done on the values. There are three categories of types which are used in most programming languages. They include base type, compound type and complex type (Yuan & Eduardo 2009). Base types are primitive types which are provided by the hardware being used. They include double, char, float int, and bool. While, compound types are constructed as aggregations of simple compound types and base types they include unions, records, arrays, structs and pointers. Complex types are recognized as abstract data types. This high level abstracts are not in all programming languages being used some may have while others may not. They include; tables, lists, queues, stacks, heaps and trees. An example of Semantic analysis method is Latent Semantic Analysis (LSA) which is methods and theories which are used for representing contextual usage of words meaning by use of statistical computation that are applied to a large presentation of text (Guichun, 2009). It checks on similarity of words being used and identify whenever they are not similar. The decision making is based on determination of similarity of words which are being used. For it to achieve it they reflect human knowledge which is established in a variety of ways. Hence, it has some sort of intelligence like human brain for example when analyzing it does mimic human word sorting criteria and category judgments. LSA is much similar to neural net models which are based on singular value decomposition technique which is closely similar to the applicable text when comparing word and passage meaning to evaluate if they are similar. There are two ways which LSA would be constructed; as a model of computational representations underlying substantial portions of knowledge utilization and portions of acquisition and the second one is practical expedient which obtain approximate estimates mainly used on contextual usage substitutability of words which are in larger text segments. Geographic Information Systems for spatial data Geographic Information Systems (GIS) is an analytical system which captures data, stores it, analyze it, manage and make its presentation of the processed information which is linked to the location which is being analyzed. GIS is mapping software which is used to assist indecision making after collection of geographical data (Reibel, 2007). Its applications are widely used in land surveying, remote sensing, aerial photography and mathematics where it used to solve spatial data problems. Spatial data is essential to the investigation of most of the particular social demographic phenomena and how is relates to the dynamic processes of population change in the areas being studied. The system is set to be able to analyze on geographic information which are used to integrate the information, analyze it, store and share it out hence allowing users to create interactive queries and finally represent the results of all the operations being used. GIS is also referred to the science which underlay geographic concepts applications and systems are used to analyze statistical data. Its data presentation is mainly in real world objects such as elevation, land use, roads which are used in real world objects which would be divided into abreactions; in continuous fields and such as rain fall and discrete objects such as houses. These data is the one which acts as inputs of to GIS for processing to formulate solutions. It also uses Raster date type which is any form of digital images which are presented in grids such as an aerial photograph would represent the data being used. Vectors are also used to aid in decision making using vectors, vectors are considered as geometrical shapes with different geographical features which are expressed by different types of geometry. They include point, lines or poly lines and polygons. The lines are used in zero dimensional pints and are expressed as a single point reference such as a well. While lines and poly lines are used to present linear features such as the roads, trails, rivers or other features which are in linear position. Polygons are used on two dimensional features which covers an area on the earth surface such as lakes or city boundaries. All this attributes are the one which are feed in GIS to provide decisions based on their settings. Conclusions Use of business intelligent systems is applicable in different business environments as it has been demonstrated in this assignment, but its applications are much relevant to what is being done in the business. Most of business environment are keen in improving the quality of services they offer due to unformed clientele who are aware of their needs and insists on quality and reliability. For operations to be reliable, accurate and dependent it must utilize use of business intelligent to make it more applicable in their operations. They also make work easier and do a lot of functions within a very short time as compared to human beings or other operations. References Delorme, A. (2008). Statistical Methods. Retrieved on December 08, 2009 http://www.scribd.com/doc/4424598/STATISTICAL-METHODS Guichun, G. (2009). Semantic The Semantic Analysis Method And The Progress Of Scientific Realism. Research Center for Philosophy of Science and Technology . 30, (3) 75 – 92 Reibel, M. (2007). Geographic Information Systems and Spatial Data Processing in Demography. Population Research and Policy Review. pp. 601-618 Yuan, X & Eduardo B. (2009). Semantic Analysis Patterns. Retrieved on December 08, 2009 from http://www.cse.fau.edu/~ed/SAPpaper2.pdf Read More