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Business Analytics > Finals M1 > Flashcards

Finals M1 Flashcards

1
Q

Three Terms in Business Literature are often related to one another

A

Analytics
Business Analytics
Business Intelligence

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2
Q

Begins with a data set (a simple collection of data or a data file) or commonly with a database (a collection of data files that contain information on people, locations, and so on).

A

Business Analytics

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3
Q

A simple collection of data or a data file

A

data set

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4
Q

A collection of data files that contain information on people, locations, and so on.

A

database

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5
Q

As databases grow, they need to be stored somewhere.

A

True

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6
Q

Hardware and software used for data remote storage, retrieval, and computational functions

A

computer clouds

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7
Q

A collection of databases used for reporting and data analysis store data.

A

data warehousing

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8
Q

Database storage areas have become so large that a new term was devised to describe them.

A

True

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9
Q

Describes the collection of data sets that are so large and complex that software systems are hardly able to process them .

A

Big data

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10
Q

They define ________ as anything that is not big data.

A

little data

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11
Q

describes the smaller data segments or files that help individual businesses keep track of customers.

A

Little data

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12
Q

Using analytics as a means of sorting through data to find useful information, the application of analytics has found a new purpose.

A

True

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13
Q

Can be defined as a process that involves the use of statistical techniques (measures of central tendency, graphs, and so on), information system software (data mining, sorting routines), and operations research methodologies (linear programming) to explore, visualize, discover and communicate patterns or trends in data.

A

analytics

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14
Q

measures of central tendency, graphs, and so on

A

statistical techniques

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15
Q

information system softwares:

A

data mining, sorting routines

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16
Q

operations research methodologies aka?

A

linear programming

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17
Q

can be defined as a process that involves the use of statistical techniques, information system software , and operations research methodologies to explore, visualize, discover and communicate patterns or trends in data.

A

Analytics

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18
Q

Analytics is an older term commonly applied to all disciplines, not just business.

A

True

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19
Q

convert data into useful information.

A

analytics

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20
Q

Three types of analytics

A

descriptive , predictive , and prescriptive

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21
Q

The application of simple statistical techniques that describes what is contained in a data set or database.

A

Descriptive analytics

22
Q

An application of advanced statistical, information software, or operations research methods to identify predictive variables and build predictive models to identify trends and relationships not readily observed in a descriptive analysis.

A

Predictive analytics

23
Q

An application of decision science, management science, and operations research methodologies (applied mathematical techniques) to make best use of allocable resources.

A

Prescriptive analytics

24
Q

To identify possible trends in large data sets or databases.

A

Descriptive analytics

25
Q

To build predictive models designed to identify and predict future trends.

A

Predictive Analytics

26
Q

To allocate resources optimally to take advantage of predicted trends for future opportunities.

A

Prescriptive Analytics

27
Q

________________ statistics, including methodologies like:

measures of central tendency (mean, median, mode)
measures of dispersion (standard deviation)
charts
graphs
sorting methods
frequency distributions
probability distributions
sampling methods

A

Descriptive

28
Q

____________statistics, uses:

Multiple regression

ANOVA

Information system methods like data mining and sorting.

Operations research methods like forecasting models.

A

Predictive

29
Q

________________ statistics, uses operations research methodologies like linear programming and decision theory.

A

Presciptive

30
Q

answers the questions what happened and why it happen

A

Descriptive analytics

31
Q

What exactly is the problem?
How many, how often, where?
What happened?

A

Descriptive analytics

32
Q

answers the question what will happen:

A

predictive analytics

33
Q

What will happen next if…?
What if these trends continue?
What could happen…?
What actions are needed?

A

predictive analytics

34
Q

Anticipates what will happen, when it happened, and also why it happened:

A

prescriptive analytics

35
Q

How can we achieve the best outcome including the effects of variability?
How can we achieve the best outcome?

A

prescriptive analytics

36
Q

____________ is focused on generating insightful information from data sources

A

analytics

37
Q

____________________ goes the extra step to leverage analytics to create an improvement in measurable business

A

business analytics

38
Q

the three types of analytics are applied sequentially (descriptive, then predictive, then prescriptive).

A

True

39
Q

can be defined as a process beginning with business-related data collection and consisting of sequential application of descriptive, predictive, and prescriptive major analytic components, the outcome of which supports and demonstrates business decision-making and organizational performance.

A

BA

40
Q

Policing/Security
Transportation
Fraud and Risk Detection
Manage Risk
Delivery Logistics
Web Provision
Proper Spending
Customer Interactions
City Planning
Healthcare
Travel
Energy Management
Internet/Web Search
Digital Advertisement

A

Where is Analytics Applied

41
Q

____________ will translate the business challenges into operational measures that can be monitored over time, not only for analytics impact, but for the entire company.

A

Metrics

42
Q

is a data point at a single point in time

A

Measurement

43
Q

Metrics is Measurement with context

A

True

44
Q

Measurement is Metrics with context

A

False

45
Q

____________ means by which your company can measure progress and business analytics impact.

A

Objective

46
Q

When is Analytics Not Practical?

A

When There’s No Data

When There’s No Precedent

When the Decision Maker Has Considerable Experience

When the Variables Can’t Be Measured

47
Q

The Three Secret of Success

EUR

A

Establish business analytic culture
Understand analytic in play
Recognize the insights as a competitive advantage.

47
Q

Challenges of Business Analytics

ECC

A

Environment
Competition
Customers

48
Q

Predictive analytics methodologies

MR
A
DMDS
FM

A

Multiple regression

ANOVA

Information system methods like data mining and sorting.

Operations research methods like forecasting models.

49
Q

Prescriptive analytics methodologies

A

Decision Theory
Linear Programming

Business Analytics (4 decks)

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