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ISTM 210 > chapter seventeen > Flashcards

chapter seventeen Flashcards

1
Q

Business Intelligence

A

an assortment of software applications used to analyze an organization’s raw data

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2
Q

data

A

raw, unorganized facts

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3
Q

information

A

processed data that means something

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4
Q

ROI

A

return on investment

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5
Q

you want to use data in a _____ way

A

predictive

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6
Q

Decision Support Systems (DSS)

A

computer-based systems that support an organization’s decision-making activities

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7
Q

Big Data

A

smartphone metadata, Internet usage records, social media activity, computer usage records, and countless other data sources

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8
Q

Structured Data

A

resides in fixed formats
well labeled
standard format, recognizable patterns

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9
Q

Unstructured Data

A

disorganized data that cannot be easily read or processed by a computer because it is not stored in rows and columns

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10
Q

What percent of data is unstructured?

A

80%

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11
Q

semi-structured data

A

lands somewhere in-between structured and unstructured data and can possibly converted into structured data

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12
Q

what are the four Vs of Big Data?

A

volume, velocity, variety, and varacity

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13
Q

volume

A

the sheer quantity of data

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14
Q

velocity

A

the speed to gather and process all of the data

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15
Q

variety

A

what kind of data

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16
Q

veracity

A

is the data collected any good?

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17
Q

what’s the first step of collecting internal data?

A

take inventory of data-> who or what makes it

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18
Q

Customer Relationship Management (CRM)

A

contains information about an organization’s sales, marketing, customer service records, etc.

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19
Q

Marketing Automation Services

A

data resides in this system that has endless customer facts and figures

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20
Q

Social Media Platforms

A

can uncover what your customers are thinking

21
Q

what percent of data is unstructured?

A

80%

22
Q

jeopardy

A

doesn’t ask its contestants to provide answers, it asks for the questions
DECIDE HOW MUCH DATA

23
Q

data warehouses

A

where an organization stores and consolidates data in a central location

24
Q

it is not unusual for data warehouses to hold ______ of data

A

yottabytes

25
Q

datamart

A

smaller organizations use this smaller, more focused data warehouse (cheaper, but limit the complexity of databases)

26
Q

Extract, Transform, and Load (ETL)

A

used to standardize data across systems that allow it to be queried

27
Q

querying

A

ask data questions->answers->decisions

28
Q

ETL must happen in order

A

extract data, transform to fit in data warehouse, load the data into warehouse

29
Q

where does data typically reside?

A

Customer Relationship Management (CRM) or Enterprise Resource Planning (ERP)

30
Q

what is one of the ERPs main function?

A

centralize an organization’s data so that it ends up being a wealth of data with value across the organization

31
Q

normalizing data

A

data is typically organized into the fields and records of a relational database->STANDARDIZED FORMAT

32
Q

load

A

the more often this is done, the more up-to-date analytic reports are possible

33
Q

ETL can eat ______ and _______

A

bandwidth and storage at an alarming rate and size

34
Q

hadoop

A

an infrastructure for storing and processing large sets of data across multiple servers

35
Q

what animal is Hadoop?

A

a toy elephant owned by Doug cuttings son

36
Q

Hadoop is best for…

A

large companies that have data scientists to run it

37
Q

if ETL brings the mountain to mohammed, then Hadoop…

A

brings mohammed to the mountain

38
Q

map reduce

A

the processing arm, or engine of Hadoop

saves bandwidth

39
Q

what does map reduce do?

A

allows data to be queried and processed directly on the server where it lives, instead of moving the data across the network to be analyzed on the compute

40
Q

data analysis

A

make sense of an organizations’s collected data and turn it into useful information

41
Q

data mining/data discovery

A

identify outliers

42
Q

topic analytics

A

catalog phrases of feedback to relevant topics

43
Q

text analytics/text mining

A

hunts through unstructured text data to look for useful patterns

44
Q

business analytics

A

attempts to make connections between data so organization’s can try to predict future trends that may give them a competitive advantage

45
Q

descriptive analytics

A

defines past data so that it can be grouped

46
Q

predictive analytics

A

attempts to reveal future patterns

47
Q

decision analytics

A

looks at an organization’s internal data and then analyzes external conditions to endorse a best course of action

48
Q

data visualization

A

graphic display of the results of data mining and analytics

49
Q

dashboards

A

easy-to-use graphical interfaces that characterize specific data analysis through visualization

ISTM 210 (23 decks)

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