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Big Data > Intro to Big Data Final > Flashcards

Intro to Big Data Final Flashcards

1
Q

What is business intelligence?

A

An umbrella term that combines architectures, tools, databases, analytical tools, applications and methodologies.

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2
Q

What is the major objective of business intelligence?

A

To enable interactive, sometimes real time data to give business managers and analysts the ability to conduct appropriate analyses

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3
Q

What is the process of BI based upon?

A

Transformation

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4
Q

Who came up with the term Business Intelligence, and when?

A

Gartner Group in the mid-1990s

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5
Q

What are the four major components of a BI system?

A

A DW
Business analytics
BPM
User interface / dashboard

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6
Q

What legislation requires business leaders to document their business processes and sign off on their legitimacy?

A

Sarbanes-Oxley Act

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7
Q

What is BI not?

A

Transaction processing

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8
Q

What is OLTP?

A

Online transaction processing, a system that handles a company’s routine ongoing business. Store SCM & CRM data

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9
Q

What is OLAP

A

Online analytical processing systems, use DW

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10
Q

What is BAM?

A

Business activity management

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11
Q

What are shells?

A

Preprogrammed tools where all you have to do is insert your numbers

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12
Q

What is the definition of analytics?

A

The process of developing actionable decisions or recommendations for actions based on insights generated from historical data

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13
Q

What are the three levels of Business Analytics?

A

Descriptive, Predictive, Prescriptive

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14
Q

What are descriptive analytics?

A

Reporting analytics, knowing what is happening in the organization and understanding some underlying trends and causes of such occurrences

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15
Q

What are predictive analytics?

A

They aim to determine what is likely to happen in the future

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16
Q

What are prescriptive analytics?

A

goal is to recognize what is going on as well as the likely forecast and make decisions to achieve the best performance possible (aka decision or normative analytics)

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17
Q

What is a data warehouse?

A

DW is a pool of data produced to support decision making; it is also a repository of current and historical data of potential interest to managers throughout the organization

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18
Q

What is teradata?

A

symbolize the ability to manage terabytes (trillions of bytes) of data

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19
Q

What are the characteristics of Data Warehousing?

A 
Subject oriented (comprehensive view of org)
Integrated
Time variant (time series)
Nonvolatile
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20
Q

What is a data mart?

A

a smaller version of a DW that focuses on a particular subject or department

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21
Q

What is a dependent data mart?

A

DM created directly from the Data Warehouse

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22
Q

What is an independent data mart?

A

Small warehouse designed for a strategic business unit or a department but its source is not an EDW

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23
Q

What is an Operational Data Store?

A

provides a fairly recent form of customer information file
updated throughout the course of business operations
used for short-term decisions

24
Q

What are oper marts?

A

created when operational data needs to be analyzed multidimensionally

25
Q

What is EDW?

A

Enterprise data warehouse

large-scale data warehouse that is used across the enterprise for decision support

26
Q

What is Metadata?

A

Data about data
describe the structure of and some meaning about data
usually either technical or business metadata

27
Q

What are the text mining techniques?

A
  1. Term frequency-Inverse document frequency
  2. Named entity recognition
  3. Topic modeling
  4. Event extraction
28
Q

What is TF-IDF?

A

Term frequency-Inverse document frequency
looks at how frequently a word appears in a document and relative to the whole set of documents
Used to build classifiers or predictive models

29
Q

What is NER?

A

Named entity recognition

Recognizes nouns and could be used to extract persons, organizations, locations, dates, monetary amounts

30
Q

What is topic modeling?

A

Identifies dominant themes in a vast array of documents

31
Q

What is Latent Dirichlet Allocation?

A

words automatically clustered by mixture of topics in each document

32
Q

What is probabilistic latent semantic indexing?

A

models co-occurring probability

33
Q

What is event extraction?

A

A step further than NER and harder
It looks at the relationship between nouns
looks at kinds of inferences that can be made from incidents in the text

34
Q

What is the text mining process?

A
  1. Establish the Corpus: Collect & Organize the Domain Specific Unstructured Data
  2. Create the Term-Document Matrix: Introduce the structure to the Corpus
  3. Extract Knowledge: Discover Novel Patterns from the T-D Matrix
35
Q

What is Web Usage Mining?

A

extraction of information from data generated through web page visits and transactions

36
Q

What is the goal of sentiment analysis?

A

What do people feel about a certain topic?

37
Q

What are the characteristics of Big Data?

A 
Volume
Variety
Velocity
Variability
Veracity
Value
38
Q

What is Hadoop?

A

An open source framework for storing, analyzing massive amounts of distributed, unstructure data

39
Q

What are the Big Data core technologies?

A

MapReduce + Hadoop

40
Q

What is MapReduce?

A

A programming model that distributes processing of very large multi-structured data files across a large cluster of ordinary machines/processors. Developed and popularized by Google.

41
Q

What are data mining characteristics?

A
  1. Source of data for DM is often a consolidated data warehouse
  2. DM environment is usually a client-server of a web-based information systems architecture
  3. Data for DM includes only structured data
  4. The miner is always an end user
42
Q

What are the most common standard processes for data mining?

A
  1. CRISP-DM

2. SEMMA

43
Q

What is CRISP-DM?

A

Cross-Industry Standard Process for Data Mining

44
Q

What is SEMMA?

A

Sample, Explore, Modify, Model, and Assess

45
Q

What are the phases for data mining?

A
  1. Define the problem
  2. Identify required data
  3. Prepare and pre-process
  4. Model the data
  5. Train and test
  6. Verify and deploy
46
Q

What is simple split?

A

splitting the data into 2 mutually exclusive sets training (~70%) and testing (30%)

47
Q

What are the data mining methods?

A
  1. Classification
  2. Regression
  3. Cluster
  4. Association Rule Mining
48
Q

What are the types of Business Reporting?

A
  1. Metric Management Reports
  2. Visualizations/Dashboard
  3. Balanced Scorecard
49
Q

What does a balanced scorecard do?

A

Translates an organization’s financial, customer, internal process into a set of actionable initiatives.

50
Q

What is the definition of data?

A

A collection of facts usually obtained as a result of experiences, observations, or experiments

51
Q

What are inferential statistics?

A

Drawing inferences about the population based on sample data

52
Q

What is a histogram?

A

A frequency chart

53
Q

What is Kurtosis?

A

detects the peak/tall/skinny nature of distribution

54
Q

What is skewness?

A

Measure of asymmetry

55
Q

What is regression?

A

a part of inferential statistics, used to characterize relationship between explanatory (input) and response (output) variable

Big Data (1 decks)

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