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BA_EM Electronic Marketing. 22. 10. 2013 – Pavel Kotyza @V ŠFS. Agenda. Effective data mining as a source of relevant data about customer needs. What is data mining?. Absolut Unknown Useful. What is data?. Data-mining traditional uses. Data-mining traditional uses.

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Ba em electronic marketing

BA_EM Electronic Marketing

22. 10. 2013 – Pavel Kotyza @VŠFS


Agenda
Agenda

  • Effective data mining as a source of relevant data about customer needs


What is data mining
What is data mining?

  • Absolut

  • Unknown

  • Useful








Question
Question

  • Say an example of data mining?



What is data mining1
What is data mining?

  • Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis.

  • Data mining uses sophisticated mathematical algorithms to segment the data and evaluate the probability of future events.

  • Data mining is also known as

    • Knowledge Discovery (KD) in Data (KDD).


The key properties of data mining are
The key properties of data mining are

  • Automatic discovery of patterns

  • Prediction of likely outcomes

  • Creation of actionable information

  • Focus on large data sets and databases


Video
Video

http://www.youtube.com/watch?v=BjznLJcgSFI


Why to use
Why to use

  • Data mining can answer questions that cannot be addressed through simple query and reporting techniques.


Video example
Video example

  • http://www.ted.com/playlists/56/making_sense_of_too_much_data.html



Automatic discovery
Automatic Discovery

  • Data mining is accomplished by building models. A model uses an algorithm to act on a set of data. The notion of automatic discovery refers to the execution of data mining models.

  • Data mining models can be used to mine the data on which they are built, but most types of models are generalizable to new data. The process of applying a model to new data is known as scoring.


Prediction
Prediction

  • Many forms of data mining are predictive.

  • E.g. A model might predict income based on education

  • Predictionshave an associated probability (How likely is this prediction to be true?). Prediction probabilities are also known as confidence

    • How confident can I be of this prediction?

  • Some forms of predictive data mining generate rules, which are conditions that imply a given outcome.

  • E.g. A rule might specify that a person who has a bachelor's degree and lives in a certain neighborhood is likely to have an income greater than the regional average. Rules have an associated support

    • What percentage of the population satisfies the rule?


Grouping
Grouping

  • Other forms of data mining identify natural groupings in the data.

  • E.g. A model might identify the segment of the population that has an income within a specified range, that has a good driving record, and that leases a new car on a yearly basis.


Actionable information
Actionable Information

  • Data mining can derive actionable information from large volumes of data.

  • For example, a town planner might use a model that predicts income based on demographics to develop a plan for low-income housing.

  • A car leasing agency might a use model that identifies customer segments to design a promotion targeting high-value customers.


Why is it important now
Why is it important now

  • Data all around us

  • Social networks

  • Search in e-shops

  • Targeting Advertising

  • Information overload


Social insight personal advantage
Social Insight & Personal Advantage

  • Rent prices

  • Blogs and News

  • Movie data

  • Fashion

  • Product Prices

  • Hotties / Adult content categories


The beauty of data visualization
The beauty of data visualization

http://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization.html






Data gathering preparation
Data Gathering & Preparation

  • Data Access

  • Data Sampling

  • Data Transformation


Model building evaluation
Model Building & Evaluation

  • Create Model

  • Test Model

  • Evaluate & Interpret Model


Knowledge deployment
Knowledge Deployment

  • Model Apply

  • Custom Reports

  • ExternalApplications


How predictable are you
How predictable are you?

http://www.youtube.com/watch?v=DaWcL3oOd-E


The end
The End!

  • Are there in your company/school any assholes?Solution: of the problem:

    • D-Fenz Tie Test - Extreme example


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