finals minsan Flashcards

1
Q

Used to understand current business processes and plan for future changes in response to their internal and external environment

A

prescriptive analytics

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2
Q

can help attempt to explain behavior and help make decisions in the face of an uncertain future

A

prescriptive analytics

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3
Q

associated with area of OPERATIONS MANAGEMENT

which considers the transformation of materials, information, customers into goods and services

A

business process management (bpm)

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4
Q

a discipline that is focused on the use of business processes as a way of improving organizational performance

A

business process management (bpm)

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5
Q

these is a key aspect of BOTH operations management and BPM

A

performance measures

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6
Q

give examples of performance measures

A

metrics of cost, quality, speed, flexibility, and dependability

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7
Q

the use of modeling and statistics from information systems capabilities such as the storage of BIG DATA in order to TRANSFORM IT into ACTIONS through ANALYSIS and INSIGHTS in the context of organizational decision making

A

business analytics

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8
Q

this is a key part of analytics to assess business performance

A

the use of performance measures

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9
Q

this is the use of reports and visual displays to EXPLAIN and UNDERSTAND PAST and CURRENT business performance.

often contains STATISTICAL SUMMARIES that are intended to PROVIDE an OUTLINE OF TRENDS in current and past performance

A

descriptive analytics

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10
Q

ability to RECOMMEND A CHOICE OF ACTION from PREDICTIONS of FUTURE PERFORMANCE

this is done through RECOMMENDING AN OPTIMUM DECISION through MODEL DRIVEN APPROACHES to TRY OUT many different scenarios

A

prescriptive analytics

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11
Q

aims to DERIVE a DESCRIPTION OF BEHAVIOR from OBSERVATIONS so that it can DESCRIBE HOW that SYSTEM BEHAVES under DIFFERENT CONDITIONS OR SCENARIOS

A

data driven modeling approach

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12
Q

a WAY to build a model that ALLOWS US to MAKE PREDICTIONS

this is achieved through ASSOCIATIONS, SEQUENCES, CLASSIFICATION, AND CLUSTERING OF DATA

A

pattern recognition

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13
Q

aims to DERIVE a DESCRIPTION of BEHAVIOR from OBSERVATIONS of a SYSTEM so that it can DESCRIBE how that SYSTEM BEHAVES under different conditions and scenarios

A

model driven modeling

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14
Q

regression analysis, econometric modeling, time series experiments, and yield management

A

data driven analysis techniques

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15
Q

IDENTIFYING PATTERNS in COMPLEX and ILL DEFINED data sets

it involves ESTABLISHIN RELATIONSHIPS about items THAT OCCUR at a PARTICULAR POINT in time

A

data mining

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16
Q

using a data driven approach, this can GENERATE algorithms that may PROVIDE PREDICTIONS

A

machine learning

17
Q

to present LARGE SCALE DATA in some VISUAL FORM

A

visual analytics

18
Q

using DESIGNED COMPUTATIONAL EXPERIMENTS to GROW DATA which can then be ANALYZED using statistical and visualization techniques to OBTAIN INSIGHT into COMPLEX SYSTEMS

A

data farming

19
Q

it uses a MODEL the can be defined as a SIMPLIED REPRESENTATION of a real system that is USED to IMPROVE our UNDERSTANDING of the REAL SYSTEM.

this INVOLVES deciding WHAT IS RELEVANT to MEET AIMS of the CURRENT INVESTIGATION

this PROVIDES information for DECISION MAKING that CAN BE USED to MAKE PREDICTIONS of REAL WORLD DECISIONS

A

model driven analysis