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Data mining basic fundamentals

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Siddique Ibrahim
Siddique Ibrahim

data mining, data preprocessing, data cleaning, knowledge discovery, association, classification, clustering, introduction, why data mining, application

Technologie
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Data Mining Fundamentals Presented by S.P. Siddique Ibrahim AP/CSE Kumaraguru College of Technology 09/06/18 1
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DATA • Fact, Numbers (or) text. • Different format and different databases. • Examples: • College department,CoE,Hostal, Payroll, • Police traffic, fraud data • RTO • Revenue 09/06/18 3
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DATA Contd., • Operational or Transactional – sales, cost, inventory, payroll • Non operational- industry sales , forecasting data, micro economic data • Meta data – logical database design (or) dictionary design 09/06/18 5
Information • The pattern, relationships among all this data can provide information. • Example: • Analysis retail point of sale transaction • Product –selling and date 09/06/18 6
Knowledge • Information can be converted into knowledge about historical patterns and future trends. • Example: • Summary information of petrol/Diesel usage. 09/06/18 7
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09/06/18 10 / media/siddique/Files1/Kct/Siddique/Datami ning Lab/id93_480x480.jpg
General Definition of Mining • Mining is the process of extracting commercially valuable minerals resources from earth’s surface. • -Stones • -Ores • -Solid Fuels • -Crude Oil  Surface Mining  Subsurface mining 09/06/18 11
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Definition contd., • Analyzing data from different perspective and summarize information. • Information-revenue • Technically, it is the process of finding correlation (or) patterns among dozens of fields in large relational databases. • Example: Purchase pattern, credit card 09/06/18 14
Data Mining • Data mining, “the extraction of hidden predictive information from large databases”. • It is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. • The main focus of data mining process is to obtain information from the data and converted it into an knowledgeable and reasonable structure for further use. 09/04/18 15 09/06/18 15
Different Mining in Real Time 09/06/18 16
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Data set bank-data.csv 09/06/18 18
What is Machine Learning?? Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" with data, without being explicitly programmed. 09/06/18 19
Why data mining for you? • Research Opportunities. • High Opening. • Handling Big data. • Analysis capability • Future 09/06/18 20
What can data mining do? • Company competition • Internal and external factor • Analyze real feelings of customer/Auditions 09/06/18 21
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What is pattern? How it would be? • Customer buying pattern • Mobile pattern • Bus ticket booking • Cricket analysis • Political parties election freebies • Credit card 09/06/18 24
Amazon recommendation Big Bazar 09/06/18 25
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Password Hacking ATM Machine-Fraud 09/06/18 29
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What is Data Warehouse???? A data warehousing is a technique for collecting and managing data from varied sources to provide meaningful business insights. Online Airline/Bus/Railway ticket booking 09/06/18 32
Data warehouse • Centralized storage • Free use of data 09/06/18 33
How does data mining work? • Classes – stored data is used to locate data in predetermined groups. • Example: • Restaurant chain 09/06/18 34
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What is this? Classify it!!!! 09/06/18 36
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Can u able to Identify Now!!?? 09/06/18 38
Cluster • Data items are grouped based on similarity(logical relationship) (or) consumer preferences. • • Example: • Data used for market segments 09/06/18 39
Association • Mined for associations. Example: Market basket analysis 09/06/18 40
Sequential patterns • Data is mined to anticipate behavior patterns and trends. 09/06/18 41
Regression Analysis • A measure of the relation between the mean value of one variable(E.g. Output) and corresponding values of other variables(E.g Time and cost) 09/06/18 42
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https://create.kahoot.it/kahoots/my-kahoots 09/06/18 59

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