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NSG 3039 WEEK 5 QUIZ / NSG3039 WEEK 5 QUIZ (LATEST, 2020): INFORMATION MANAGEMENT AND TECHNOLOGY: SOUTH UNIVERSITY |100% CORRECT ANSWERS, DOWNLOAD TO SCORE A| $8.49   Add to cart
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NSG 3039 WEEK 5 QUIZ / NSG3039 WEEK 5 QUIZ (LATEST, 2020): INFORMATION MANAGEMENT AND TECHNOLOGY: SOUTH UNIVERSITY |100% CORRECT ANSWERS, DOWNLOAD TO SCORE A|

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  • Course
  • NSG3039 (NSG3039)
  • Institution
  • SOUTH UNIVERSITY

NSG 3039 WEEK 5 QUIZ / NSG3039 WEEK 5 QUIZ (LATEST, 2020): INFORMATION MANAGEMENT AND TECHNOLOGY: SOUTH UNIVERSITY |100% CORRECT ANSWERS, DOWNLOAD TO SCORE A|

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  • August 25, 2020
  • 19
  • 2020/2021
  • Exam (elaborations)
  • Questions & answers

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  • download to score a|
  • nsg 3039 week 5 quiz nsg3039 week 5 quiz latest
  • 2020 information management and technology south university |100 correct answers

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  • SOUTH UNIVERSITY
  • NSG3039 (NSG3039)
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NSG 3039 WEEK 5 QUIZ


1._______ ________ is an analytic, logical process with the ultimate goal of forecasting or

prediction.

 Data mining <Data mining is the analytic, logical process of using software to sort through

data to discover patterns and ascertain or establish relationships.>


 Knowledge discovery <As opposed to an analytic, logical process, knowledge discovery is

used to help to improve healthcare policy making, healthcare practices, disease prevention,

detection of disease outbreaks, prevention of sequelae, and prevention of in-hospital

deaths.>


 Data exploration <As opposed to an analytic, logical process, data exploration begins with

exploring and preparing the data for the data mining process.>


 Big data <As opposed to an analytic, logical process, big data are voluminous amounts of

data sets that are difficult to process using typical data processing.>


Answer A



 ________ ________ is key, since data mining looks at the data from different vantage

points, aspects and perspectives and brings new insights to the data set.

 Data mining <Data mining is the analytic, logical process of using software to sort through

data to discover patterns and ascertain or establish relationships.>


 Knowledge discovery <Knowledge discovery is key, since data mining looks at the data

, from different vantage points, aspects and perspectives and brings new insights to the data

set. Knowledge discovery is used to help to improve healthcare policy making, healthcare

practices, disease prevention, detection of disease outbreaks, prevention of sequelae, and

prevention of in-hospital deaths.>


 Data exploration <As opposed to a process that bring new insights, data exploration begins

with exploring and preparing the data for the data mining process.>


 Big data <As opposed to a process that bring new insights, big data are voluminous

amounts of data sets that are difficult to process using typical data processing.>


Answer B



 Much of our ______ _______ is unstructured and resides in text files representing more

than 75% of an organization‟s data. This data is not contained in databases and can be

easily overlooked. It is important since we can identify patterns and provide meaningful

insights.

 data mining <As opposed to being a body of raw facts, data mining is the analytic,

logical process of using software to sort through data to discover patterns and ascertain

or establish relationships.>

 knowledge discovery < As opposed to being a body of raw facts, knowledge discovery

is used to help to improve healthcare policy making, healthcare practices, disease

prevention, detection of disease outbreaks, prevention of sequelae, and prevention of

in-hospital deaths.>

 data exploration <As opposed to being a body of raw facts, data exploration begins

, with exploring and preparing the data for the data mining process.>

 big data < Big data are voluminous amounts of data sets that are difficult to process

using typical data processing.>

Answer D



 _________ _________ is a data driven method to eliminate defects, waste, or assess

quality control issues. It is aimed at decreasing disparities in a business and manufacturing

process through dedicated improvements.

 Six Sigma <Six Sigma is a data driven method to eliminate defects, waste, or assess

quality control issues.>

 CRISP-DM < Rather than a data-driven model, the CRISP-DM model follows a path or

series of steps to develop a business understanding by gaining an understanding of the

business data collected and analyzed.>

 SEMMA Explore <While similar to a data-driven model, SEMMA (sample, explore,

modify, model, assess) refers to the core process of conducting data mining,

concentrating more on the technical activities characteristically involved in data

mining.>

 Data Exploration <Rather than being a method of removing defects, data exploration

begins with exploring and preparing the data for the data mining process.>

Answer A



 We must not only be able to extract meaningful information and knowledge but also be

able to _______ and _______ what we are learning, the new knowledge we are generating.

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