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.
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.
