Data Mining and Knowledge Discovery Techniques
Added on 2020-04-15
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Running head: OVERVIEW OF THE BUSINESS OPERATIONSOverview of the business operationsName of the StudentName of the UniversityAuthor Note
OVERVIEW OF THE BUSINESS OPERATIONS2(A) Summary ReportThis section of the assignment gives a summary report of the business operations thatare the Business Intelligence (BI), Data Mining (DM) and Knowledge Discovery inDatabases (KDD).Business Intelligence (BI)Business Intelligence or BI is one of the renowned operations to be used in thebusiness considering the modern day situations of the commercial market. The other name bywhich Business Intelligence is known in the market of business and commerce is DescriptiveAnalysis. It is named so because it describes the past or the current state of the runningbusiness operations (Sauter, 2014). It is that wing of the business that is confined todescribing what were the conditions of the business and what is the present conditions of thebusiness. Technically speaking it can be said that business intelligence is a customary ofsome specific processes, some critical architectures and some of the profound technologiesthat is confined to converting raw data into meaningful information as a result of which it isused to drive some of the profitable business actions. It is a package that is formed with thecombination of the software and the services targeted to transform the normal data into adirectorial path of knowledge and critical insights.As mentioned above the objectives of business intelligence in are straightforward.Besides analysing what has been done and what needs to be done, there are more areas wherethe grip of Business Intelligence is substantial (Abelló et al., 2013). The impact of businessintelligence in an organisation is direct and to be confined to be benefitted with strategic,tactical and operational decisions of business. It hugely supports resource based decisionmaking using with the use of historical data and not just by relying in the assumptions and thepredictions (Debortoli, Müller & vom Brocke, 2014). The tools used in the business
OVERVIEW OF THE BUSINESS OPERATIONS3intelligence systems are used to perform certain set of operations. This set of the operationsmainly includes the creation of the reports, brief ad concise summaries, dedicateddashboards, operational maps, statistical maps and insightful charts along with theamalgamation of the detailed intelligence that is based as per the nature of the businessoperations.Business Intelligence is very much dutiful in leading out the key business operations.It is used for the creation of the key performance indicators based on the data collected in thepast. It is used for the identification and setting up of the benchmarks of several uniqueprocesses (Chang, 2014). The business intelligence systems helps out the businessorganisations to detect out the trends in the market and also find out the business problemsthat needs the critical attention from the managers. Another functionality of the businessintelligence is that it helps them on visualizing the data that helps them in enhancing thequality of the data and thereby helping them to make quality decision making. The flexibilityof the business intelligence not only assists the large enterprises but also allows an assistanceto the small and the medium scale enterprises. With the help of these kind of the modules, thebusiness intelligence proves to be fruitful to the business organisations.Data MiningData Mining is one of the many operations involved in the business processes that issimilar to that of the business intelligence operations. The operations are almost similarbecause it is also used by the business organisations to convert raw data into valuable set ofinformation. Dedicated software is used in data mining to drive out useful insights about thecompany (Lin, Yao & Zadeh, 2013). By using a special type of software to look for thepatterns in some of the sections of data, business operations will be able to learn more about
OVERVIEW OF THE BUSINESS OPERATIONS4the insightful information about their customers involved to enhance and frame out some ofthe effective marketing strategies, reduce the total costs and increase the number of sales forthe company. The main outlines of the Data Minig activities involves the processes ofeffective collection of raw data, resourceful warehousing and the processes related to thatcomputing.Warehousing is a process when the companies are involved towards centralizing theirdata into a single database or a single program. The use of the data warehouse in data miningis huge in implementing the effective processes in the organisation. It may be used by thelarge enterprises to chalk out the segments of the data that are required to perform criticalanalysis and use them accordingly in some of the specific situations (Larose & Larose, 2014).Although, in some of the other cases analysts may entail on the process of selecting dataaccording to their choices and begin with the process of data warehousing based on those setof requirements and the specifications (Freitas, 2013). It is regardless of the fact that DataMining is used by most of the organisations to carry out operations that are involved with theprocesses of tactical decision making among the management of the concerned businessorganisation. The programs that are based on the data mining processes are often used foranalysing the relationships and the patterns that are specifically based on the user requests ofa particular area.One of the instances of the use of data mining processes in the organisations statesthat the data mining process can be used by the organisations to create separate classes ofinformation. As a generic example, the online stores of the internet world can be taken up. Itis these online stores that collects the information of their valuable customers online andseparate them into unique classes where they are served with special deals according to theirlikings and the requirement pattern. The insights of the customers are analysed and stored inspecial directories with the involvement of the dedicated data mining software. These insights
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