Limited-time discount for students! | Solutions starting at $6 each

(Solved) Data Mining Process - PDF

Added on - 14 Jun 2021

  • 18


  • 2339


  • 76


  • 0


Trusted by +2 million users,
1000+ happy students everyday
Showing pages 1 to 4 of 18 pages
AimThe main goal of the Data mining process is to extract information from dataset and transforminto understandable structure. Generally the data mining techniques involves databasemanagement aspects, data pre-processing, model and inferences considerations and interestingmetrics. Data mining is the analysis step of the “Knowledge discovery in database process”.Introduction:Data miningData mining is the process of discovering patterns in large datasets and used toextract usableinformation from any raw data.It is an efficient technique to analyze and categorize the hiddenpatterns of data according to various perspectives of applications. Data mining involves someother methods to process the extracting data’s such as Data Cleaning, Data Integration, andtransformation of data, Evaluation of patterns and presentation of data. Once all these methodsare over, the extracting information’s are used in fraud detection, data analysis process and etc...The Scope of Data MiningWithin the short time data mining optimize the huge datasetIt represents the data in different perspectives of logical orderIt includes tree-shaped structure to understand the hierarchy of dataIt is used to derive the genetic way of classification of various sets of data items.Data mining has a number of functionalities belonging to two primary categories one isdescriptive and another is predictiveDescriptiveDescriptive is the clustering method which is used to identify the group of items based on somesimilar characteristicsPredictivePredictive is the classification technique which is used to predict the class attributes and basemodels and rules.
1.Data mining toolsThe design and development of several applications of data mining algorithms requires the use ofpowerful tools.Different types of data mining tools are used to design the application programfor software and hardware platforms.The data can be found through various digital tools fromdifferent sources to get raw data from digital and physical worldR-language toolRapid Miner(erstwhile YALE)WEKAPython based Orange and NTLKKnimeSisenseDataMartOracle Data MiningApache mahoutSSDT(SQL server data tools)RattleIBM cognosTeradataDundas BI2.Data mining TechniquesMany techniques are used to mine data from different platforms and various applications. Therenumber of techniques is used to evolve the data sets in various environments.Data mining techniques is the important factors for developing projects which are designed toexplore data. Data mining techniques has to be choosen based on the type of design anddevelopment.Most commonly used techniques in Data mining:StatisticsClassificationAssociationOutlier detection
ClusteringRegressionPredictionCluster analysisAnomaly detectionIntrusion detectionDecision treesNeuralnetworks3.Benefits of Data miningThe main benefit of data mining process is to discover those records of information andsummarize it in a simpler format for the purpose of others.Data mining plays a vital role incollecting, processing, storing and analyzing data in order to extract raw information fromvarious platforms. Data mining is used to create accurate models for databases. It helps toidentify the data patterns and used to discover all sorts of information. It is used toimprove the efficiency of decision making process4.Cutting edge data mining techniquesIt is one of the most popular techniques used in data mining. There are several major data miningtechniques have been developing. There are used in data mining projects. Recently adding theassociation, decision tree, classification, sequential patterns, prediction and clustering etc. Thetechniques are refers to technological devices. It is also known as leading edge technology orstate of the art technology.The technology refers to the point at which there is a gap in knowledge.Bleed edge technologyIt is a high risk technology of being unreliable. Example for electronic mail(email).Thetechnology contains degree of risk.Lack of concurrence
Leading to rapid changes. But it is very nature. The way of creating new thingsexists in the technology.Lack of testingIt is one of the unreliable or simply untested technologies.It is one of the successful technologies. It is used to establish the comparative advantages. Thebleeding edge computer software is open source software.Another one technology of cutting edge is state of the art technology. It is sometimescalled also cutting edge. It is highest level of general development. It is a scientific field achievedat a particular time.5.Real time examples for cutting edge technologyNFC technologyThe technology used in the Google billboard. Near field communication used in order toencourage the customers. It is engaged with digital billboards.Geo fencingGeo fencing is a bar gaining area for marketers. Providing a host for mingled with theconsumers. It is a real time content in a specific location.Face book hangersIt is one of the social networking applications. Avoid hacking in the process oftransformed messages.6.Applications of Data miningThe following domains are mostly used the Data mining.1.Risk management and corporate analysis.2.Fraud detection.3.Market Analysis and Management.
You’re reading a preview
Preview Documents

To View Complete Document

Click the button to download
Subscribe to our plans

Download This Document