Costarch Analytical Consulting Pvt Ltd.

Costarch Analytical Consulting Pvt Ltd.

Data MiningWhy data mining

What is data mining

Scope of data mining

Typical applications

Issues with data mining

What it is?

Data Mining Contd..A data mining research carried out at supermarkets showed that, Men who had children and who do shopping on Saturday to buy nappies for their little ones tend to buy Beer also.Interesting right?.....Lets see some more examplesData Mining Contd..helps in churn prevention.

Data mining Contd..Data mining in CRMBased on the behavior and personal data about the customer, CRM admisnitrter will divide the customer in two classes.A Prediction model can be created using this data to find the probability of losing a customer in next two years.

Data Mining Contd..IN CRM , it is a well known fact that acquiring a new customer cost 7 times more than keeping the existing customer (churn prevention)

Thus CRM can help to reduce the churn rateWhy Data Mining is important ?Data

Why Data Mining is important?

Everything is sold and advertisedon internext9Why Data MiningTerabytes of data generated every dayAbundance of data available from sources like business, society and scienceEasy techniques of data collection ex: automated data collection tools, database systems, computerized society etc Need for analysis of massive data

What is Data Mining It is a process of discovering suitable NewPotentially useful insightsUnder stable patterns and trends in the large data setsUsing sophisticated mathematical algorithmsTo segment the dataEvaluate the probability for future events Stages of Data mining

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Reasons for Data Mining popularity

Growing Data VolumeLimitations of Human AnalysisLow Cost of Machine Learning

Data Mining ModelsVerification ModelDiscovery ModelData Mining Process ModelDataScope of Data MiningData Mining technology can generate new business opportunitiesAutomated prediction of trends and behaviorsAutomated discovery of previously unknown patternsYield the benefits of automation on existing software and hardware platformsImplemented on new systems as existing platforms are upgraded and new products developed

Data Mining LimitationsData mining systems relies on databases to supply the raw data for output.Problem occurs as data bases tend to be dynamic, incomplete, noisy and largeUncertaintySize and updating problemLimited information

Techniques used in Data MiningArtificial Neural NetworksDecisions TreesGenetic AlgorithmNearest Neighbor MethodRule Induction

Artificial Neural Networks

System of interconnected neurons that can compute values from inputs by feeding information through the network.Models inspired by animal CNS , that are capable of machine learning and pattern reorganization.

19Decision TreeUses tree like model of decisions and their possible consequences

Decision support toolIncluding chance event outcomes, resource cost, utilityCommonly used in operation research, specifically decision analysis

20Genetic AlgorithmGenerate useful solutions to optimization and search problems.

mimics the process of natural evolutionbioinformatics, phylogenetics, computational science, engineering, economics, chemistry, manufacturing, physics etc..

21Nearest Neighbor Method

Classifying cases based on their similarity to other cases

Rule inductionThe extraction of useful if-then rules from data based on statistical significance.Data Mining Application Data mining techniques can be applied in various fields such as Telecommunication CRM Banking Medicine and Pharmaceuticals Insurance Management (Quality Assurance, Marketing)Travel and Tourism..

Contd..Media logistic Academic Research IT & ITES Online Portals and Social Media Channels Media and Advertising Airline Companies Sports FinanceFilm Industry and many more etc.25Contact Us If you have any questions , please let us know at info@costarch.com or Call us +91-8955678210 ORVisit our website: www.costarch.com www.pietutors.com