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Ch. 4 - Predictive Analytics I: Data Mining Process, Methods, and Algorithms Questions and Answers.

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predictive analytics in law enforcement - Answer 1. policing with less 2. new thinking on cold cases 3. the big picture starts small 4. success brings credibility 5. just for the facts 6. safer streets for smarter cities not new - Answer Although the term "data mining" is relatively new, the ideas behind it are ___ ___. statistical analysis; artificial intelligence - Answer Many of the techniques used in data mining have their roots in traditional ___________ ________ and __________ ____________ (AI). data mining (DM) - Answer - exciting technology - imperative and common practice for a vast majority of organizations - a strategic weapon for companies to compete with the giants of Amazon, Capital One, and Marriott Why is data mining gaining attention? - Answer 1. competition at the global scale 2. recognition of the value in data sources 3. availability of quality data - a large portion of "understanding the customer" can come from analyzing the vast amount of data that a company routinely collects - this has helped Amazon and many other successful businesses 4. decrease in cost - the cost of data storage has plummeted recently, making data mining feasible for more firms

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Ch. 4 - Predictive Analytics I: Data
Mining Process, Methods, and
Algorithms Questions and Answers.
predictive analytics in law enforcement - Answer 1. policing with less

2. new thinking on cold cases

3. the big picture starts small

4. success brings credibility

5. just for the facts

6. safer streets for smarter cities



not new - Answer Although the term "data mining" is relatively new, the ideas behind it are
___ ___.



statistical analysis; artificial intelligence - Answer Many of the techniques used in data
mining have their roots in traditional ___________ ________ and __________ ____________
(AI).



data mining (DM) - Answer - exciting technology

- imperative and common practice for a vast majority of organizations

- a strategic weapon for companies to compete with the giants of Amazon, Capital One, and
Marriott



Why is data mining gaining attention? - Answer 1. competition at the global scale



2. recognition of the value in data sources



3. availability of quality data

- a large portion of "understanding the customer" can come from analyzing the vast amount of
data that a company routinely collects

- this has helped Amazon and many other successful businesses



4. decrease in cost

- the cost of data storage has plummeted recently, making data mining feasible for more firms

, data mining (DM) - Answer the *nontrivial* process of identifying valid, novel, potentially
useful, and ultimately understandable patterns in data stored in structured databases



valid - Answer the discovered patterns should hold true on new data



novel - Answer previously unknown patterns are discovered



potentially useful - Answer results should lead to some business benefit



knowledge mining - Answer another name for "data mining"



data mining tools - Answer - use mathematical techniques for extracting hidden patterns for
predictive purposes



- use patterns in data to develop mathematical rules for predicting outcomes for future
observations



- are commonly used to identify customer buying patterns to increase sales and for fraud
detection, among other things



- in data mining, classification models help in prediction



- a data mining study is specific to addressing a well-defined business task, and different
business tasks require different sets of data



data - Answer the most critical ingredient for DM which may include soft/unstructured data



end user - Answer The data miner is often an ___ ____.



creative thinking - Answer Striking it rich requires ________ ________.



parallel processing - Answer Because of the large amounts of data and massive search
efforts, it is sometimes necessary to use ________ __________ for data mining.



patterns - Answer DM extracts ________ from data.



pattern - Answer a mathematical (numeric and/or symbolic) relationship among data items

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