P1-Modulo 2 : Big data analysis y technology concepts

Description

modulo 2 Big Data
Carolina Colorado
Quiz by Carolina Colorado, updated more than 1 year ago
Carolina Colorado
Created by Carolina Colorado almost 8 years ago
63
2

Resource summary

Question 1

Question
Big data analysis differs from trditional data analysis primary because
Answer
  • volume, value and varirety
  • volume, velocity and variety
  • veracity, volume and velocity

Question 2

Question
In big data analysis and analytics, a fundamental step-by-step process is needed to organize the task involved
Answer
  • retrieving, processing, producing and visualization data
  • retrieving, processing, producing and repurposing data
  • retrieving, processing, organize and repurposing data

Question 3

Question
which are 1,2 and 3 stages of bigData analysis lifecycle
Answer
  • Data analysis, data identification and ata extraction
  • bussines cased evaluation, data extraction and data analysis
  • bussines case evaluation, data identificaction and data acquisition and filtering

Question 4

Question
which are 4,5 and 6 stages of bigData analysis lifecycle
Answer
  • data analysis, data visualization & utilization of analysis results
  • data extraction, data validation & cleansing and data aggregation & representation
  • data extraction, data aggregation & representation

Question 5

Question
which are 7,8 and 9 stages of bigData analysis lifecycle
Answer
  • data analysis, data visualization and utilization of analysis results
  • data aggregation & represntation, data analyisis and data visualization
  • data identifcation, data acquisition & filtering and data extraction

Question 6

Question
The business case evaluation stage requires that a business case be ________, __________ and ______________ prior to proceeding with the actual hands-on analysis tasks.
Answer
  • organized, created and approbed
  • created, assessed and approbed
  • created, organized and analyzed

Question 7

Question
An evaluation of a Big Data analysis bussines case helps decision-makers undertand
Answer
  • the business resources that will need to be utilized and wich bussines challenges the analysis
  • the data that will need to be utilized and wich bussines challenges the analysis
  • the business resources that will need to be utilized and wich bussines objectives the analysis

Question 8

Question
The KPIs is ussefull in Business Case Evaluation
Answer
  • true
  • false

Question 9

Question
based on the business requirements documented in the _______________________________ , it can be determined whether the business problems being addresed are really Big data problems
Answer
  • use case
  • business case
  • requirements case

Question 10

Question
a bussines problem needs to be directly related to one or more of the big data characteristics
Answer
  • veracity, velocity or variety
  • value, velocity or variety
  • volume, velocity or variety

Question 11

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Another outcome in Business case evaluation is
Answer
  • determination of budget required to carry out the analysis project
  • determination of data required to carry out the analysis project
  • determination of resources required to carry out the analysis project

Question 12

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The invesment can be weighed against the expected benefits of achieving the goals
Answer
  • false
  • true

Question 13

Question
Initial iterations of the big data analysis lifecycle will not required more up-front invesment of Big Data tecnologies, products and training compared to later iterations
Answer
  • false
  • true

Question 14

Question
The data identification stage is dedicated to identifiying the _____________ required for the analysis project
Answer
  • metadata
  • datasets
  • datamart

Question 15

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identifying a wider variety of data sources may increase the probability of finding
Answer
  • hidden patterns and aggregations
  • hidden patterns and correlations
  • hidden resources and datasets

Question 16

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Can be beneficial to identify as many types of releated data sources and insights as possible, especilly when we don´t know exactly what we're looking for.
Answer
  • TRUE
  • FALSE

Question 17

Question
Depending on the business scope of analysis project and nature of business problems being adressed, the required dataset and their sourcescan be
Answer
  • structured and not structured
  • big or small of all enterprise
  • internal or external to enterprise

Question 18

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Internal dataset
Answer
  • data markets and publicly avalaible datasets
  • internal sources, such as data marts and operational system
  • embedded within blogs or other types of content-based websites

Question 19

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external datasets
Answer
  • strudtured data, unstructured data
  • data marts and operational systems
  • Case they may need to be harvested via automated tools

Question 20

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data is gathered from all of data sources that were identified during the previous stage, and is then subjected to the automated filtering of corrupt data or data that has been deemed to have no value to the analysis obvjectives
Answer
  • Data identification
  • data acquisition & filtering
  • Data aggregation & representation

Question 21

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Depending on the type of data source , data may come as a dump of files or may require API integration
Answer
  • false
  • true

Question 22

Question
in many cases , especially where external, unstructured data is concerned, some or most of the acquired data may be irrelevant (noise) and can be discarded as part of the filtering process
Answer
  • Data acquisition & filtering
  • Data extraction
  • Data validation & cleansing

Question 23

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data classified as "corrupt" can include records with missing or nonsensical values or invalid data type
Answer
  • false
  • true

Question 24

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Data thah is filtered out for one analysis may not be valueable for a different type of analysis
Answer
  • false
  • true

Question 25

Question
it is advisable to store a verbatim copy of the original dataset proceeding with the filtering.
Answer
  • To save on required storage space, the verbatim copy is compressed after storage
  • To save on required storage space, the verbatim copy is compressed before storage
  • To save on required storage space, the verbatim copy is compressed in the same time of storage

Question 26

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to be persisted once it gets generated or enters the enterprise boundary
Answer
  • internal data
  • internal and external data
  • external data

Question 27

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The data is persisted to disk prior to analysis
Answer
  • realtime analytics
  • Batch anlytics
  • realtime analytics and batch analytics

Question 28

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The data is analyzed first and then persisted to disk
Answer
  • realtime analytics
  • batch analytics
  • realtime analytics and batch analytics

Question 29

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Can be added via automation to data from both internal and external data sources to improve the classification an querying
Answer
  • info data
  • data analysis
  • metadata

Question 30

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Metadata example can include
Answer
  • datamart size and structure, source information, date and time of creation or collection, language-specific information etc.
  • database size and structure, source information, date and time of creation or collection, language-specific information etc.
  • dataset size and structure, source information, date and time of creation or collection, language-specific information etc.

Question 31

Question
it is vital that metadata be machine-readable and passed forward along subsequent analysis stages
Answer
  • false
  • true

Question 32

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This helps to maintain data provenance throughout the Big Data analysis lifecycle, wich helps establish and preserve data accuracy and quality
Answer
  • metadata
  • source information
  • date and time of creation or collection

Question 33

Question
Some of the data identified as input for the analysis may arrive in a format incompatible with the big data solution
Answer
  • true
  • false

Question 34

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the need to address disparate types of data is more likely with data from
Answer
  • internal sources
  • external sources

Question 35

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is dedicated to extracting disparate data and transforming it into a format that the underliying Big Data solution can use for the purpose of the data analysis
Answer
  • Data acquisition & filtering
  • data validation & cleansing
  • data extraction

Question 36

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The extent of extraction and transformation required depends
Answer
  • on the types of analytics and capabilities of the Big Data solution
  • bussines case
  • Data extraction

Question 37

Question
Estracting the required fields from delimited textual data (such as with web server log files) may not be necessary
Answer
  • capabilities of the Big Data Solution
  • underlying Big Data solution can already directly process those files
  • transforming it into a format that underlying Big Data solution

Question 38

Question
example of document that not need further transformation
Answer
  • XML and JSON
  • facebook and twitter
  • image and video

Question 39

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The invalid data can
Answer
  • Skew an falsify analysis results
  • Lose business objectives
  • Lose the accuracy of the analysis

Question 40

Question
data input into Big Data analyses can be unstructured without any indication of validity
Answer
  • false
  • true

Question 41

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the complexity can further make it easy to arrive at a set of suitable validation constraint
Answer
  • false
  • true

Question 42

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Is dedicated to establishing (often complex) validation rules and removing any know invalid data
Answer
  • Data acquisition and filtering
  • Data validation and cleansing
  • Data identification

Question 43

Question
Big Data solutions often receive redundant data across different datasets, this redundancy can be exploited to explore interconnected datasets in order to assemble validation parameters and fill in missing valid data
Answer
  • false
  • true

Question 44

Question
For Batch analytics, data validation and cleansing can be achieved via offline
Answer
  • data minnig
  • ELT operation
  • ETL operation

Question 45

Question
Data input in Big Data can be unstructured without any indication of validity
Answer
  • false
  • true

Question 46

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provenance can play an important role in determining the accuracy and quality of questionable data
Answer
  • false
  • true

Question 47

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data that appears to be invalid may still be valuable in that it may posses
Answer
  • most important data
  • hidden patterns an trends
  • noise

Question 48

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Data may be spread across multiple datasets, requiring that datasets be joined together via common files (date or ID)
Answer
  • false
  • true

Question 49

Question
either way a method of data ________________ is required or the dataset representing ther correct value needs to be determined
Answer
  • aggregation
  • reconciliaton
  • representation

Question 50

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Dedicated to integrating multiple datasets together to arrive at a unified view
Answer
  • Data aggregation & representation
  • Data extraction
  • Data visualization

Question 51

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Can become complicated because od differences in : although the data format may be the same, the data model may be different
Answer
  • semantics
  • BD engine
  • Data structure

Question 52

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Can become complicated because od differences in : A valuethat is labelled differently in two different datasets may mean the same thing (surname and last name)
Answer
  • BD engine
  • Semantics
  • Data structure

Question 53

Question
In data Aggregation & Representation reconciling the differences can required complex logic that is executed ___________________.
Answer
  • ETL process
  • human intervention
  • automatically

Question 54

Question
Future data analysis requirements need to be considered during the stage ___________________ to help foster data reusability
Answer
  • Data extraction
  • Data aggregation & REpresentation
  • Data validation and cleansing

Question 55

Question
whether ___________________ is required or not, it is important to understand that the same data can be stored in many different forms. One form may be better suited for a particular type of analysis than another
Answer
  • data cleansing
  • data aggregation
  • filtering

Question 56

Question
A data structured standarized by the Big Data solution can require establishing a central, standard analysis repository, such as a
Answer
  • untructured database
  • structured database
  • NoSQL database

Question 57

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the data analysis stage is dedicated to carriying out the actual analysis task, which typically involves one or more types of analytics
Answer
  • data validation %cleansing
  • Data Analysis
  • Utilization os analysis results

Question 58

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This stage can be iterative in nature, because repeated until appropiated pattern or correlation is uncovered
Answer
  • data aggregation & representation
  • Data analysis
  • Data extraction

Question 59

Question
The approach taken when carrying out this stage, data analysis, an be classified as ______________________________
Answer
  • acquisition analysis and filtering analysis
  • confirmatory analysis and exploratory analysis
  • validation analysis and cleansing

Question 60

Question
___________________________ adata analysis is a deductive approach where the cause of the phenomenon being investigated is proposed beforehand
Answer
  • Confirmatory analysis
  • Exploratory analysis
  • Data analysis

Question 61

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the proposed cause or assumption is called a
Answer
  • pattern and trend
  • deductive approach
  • hypotesis

Question 62

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data samples are tipically used
Answer
  • exploraty analysis
  • confirmatory analysis

Question 63

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unexpected findings or anomalies are usually ignored since a predetermined cause was assumed
Answer
  • true
  • false

Question 64

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is an inductive approach that is closely associated to data mining
Answer
  • exploratory data analysis
  • confirmatory data analysis
  • correlation analysis

Question 65

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this analysis provides a general direction that can facilitate the discovery of patterns or annomalies
Answer
  • confirmation analysis
  • Exploratory analysis

Question 66

Question
Large amounts of data and visual analysis are typically used
Answer
  • Confirmatory analysis
  • Exploratory analysis

Question 67

Question
is dedicated to using _____________________ techniques and tools to graphically communicate the analysis results for effective interpretation by bussines users
Answer
  • Data analysis
  • Data visualization
  • Utiolization of analysis results

Question 68

Question
Bussines users needs to be able to understand the results in order to obtain value from analysis and subsequently have de ability to provide feedback from_______________ back to stage __________________
Answer
  • Data validation and cleaning, data extraction
  • Data analysis, data aggregation & representation
  • Data visualization, Data analysis

Question 69

Question
the same results may be presented ina a number a number of different ways.
Answer
  • false
  • true

Question 70

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another aspect to keep in mind is that providing a method of drilling down to comparatively simple statistics is crucial, in order for users to understand how to statistics were generated
Answer
  • true
  • false

Question 71

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support businessdecission-making, there may be further opportunieties to utilize the analysis results
Answer
  • Utilization of analysis results
  • Data visualization
  • Data analysis

Question 72

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The utilization os analysis results is dedicated to determining how and where processed analysis data can be further leveraged
Answer
  • Utilization of analysis results
  • Data visualization
  • Data analysis

Question 73

Question
"models" that encapsulated new insights and understandings about the nature of the patterns and realationships that exist within data that was just analyzed
Answer
  • utilization of analysis results
  • Data analysis
  • Data validation &cleansing

Question 74

Question
A "model" may look like a
Answer
  • mathematical equation or a set of rules
  • structred database
  • the differents datasets

Question 75

Question
Models can be used to improved bussines process logic
Answer
  • new dataset
  • form the basis of a new system or software program
  • application system logic
  • new bussines case

Question 76

Question
the data analysis results may be automatically or manually fed directly into enterprise systems to enhace and optimize their behavior and performance
Answer
  • input for enterprise systems
  • Bussines process optimization
  • Alerts

Question 77

Question
The identiffied patterns correlations and anomalies discovered during the data analysis are used to refine business process
Answer
  • input for enterprise input
  • alerts
  • Bussines process optimization

Question 78

Question
Data analysis results can be used as input for existing events that requires them to take corrective action
Answer
  • input for enterprise input
  • business process optimization
  • alerts

Question 79

Question
Big data nalysis concepts
Answer
  • statical
  • aggregation
  • visual
  • machine learning
  • Semantic
  • Topic mapping
  • feelings

Question 80

Question
statistical analysis
Answer
  • A/B Testing
  • heat maps
  • correlation
  • Regression
  • filtering

Question 81

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visual Analysis
Answer
  • heat maps
  • outlier detection
  • time series analysis
  • Spatial Data Analysis
  • Network analysis

Question 82

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machine learning
Answer
  • correlation
  • clasification
  • clustering
  • outlier detection
  • filtering
  • regression

Question 83

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semantic analysis
Answer
  • classification
  • network analysis
  • Natural language processing
  • text analytics
  • sentiment analysis

Question 84

Question
use statistical methods based on mathematical formulas as means for analizing data
Answer
  • visual analysis
  • statistical analysis
  • machine learning

Question 85

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it can also be used to infer patterns ans relationships within the dataset, such as regression and correlation
Answer
  • statistical analysis
  • semantic analysis
  • analysis topic mapping

Question 86

Question
also know as split or bucket testing, compares two versions of an element to determine wich version is superior based on a predefined metric
Answer
  • correlation
  • A/B testing
  • regression

Question 87

Question
A/B testing: the current version of the element is called the ______________ version, whereas the modified version is called the ____________
Answer
  • official, non official
  • control,reatment
  • principal, copy

Question 88

Question
both version, are subjected to an experiment simultaneously. The observationsare recorded to determine wich version is more sccessful
Answer
  • correlation
  • Regression
  • A/B testing

Question 89

Question
Athough ________________________can be implemented in almost domain, it is most often used in marketing
Answer
  • A/B Testing
  • Regression
  • Correlation

Question 90

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Generally, the objective is to gauge human behavior with the goal of increasing sales (as per the example below)
Answer
  • Regression
  • A/B testing
  • Correlation

Question 91

Question
is the new version of a drug better than the old one?
Answer
  • correlation
  • Regression
  • A/B testin

Question 92

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is an analysis tecnique used to determine whether two variables are related to each other
Answer
  • Regression
  • Correlation
  • A/B testing

Question 93

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an example of a relationship between two variables: The value of variable A increases whenever the value of variable B increases
Answer
  • Regression
  • A/B testing
  • Correlation

Question 94

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Helps to develop an understanding of a dataset and find relationships that can assist in explaining a phenomenon
Answer
  • Correlation
  • Regression
  • A/B testing

Question 95

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commonly used for data mining where the identification between variables in a dataset leads to the discovery of patterns ans anomalies
Answer
  • regression
  • correlation
  • A/B testing

Question 96

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When two variables are considered to be correlated they are considered to be aligned based on a linear relationship
Answer
  • false
  • true

Question 97

Question
This mean that when one variable changes, the other variable also changes proportionally and constantly
Answer
  • A/B testing
  • regression
  • correlation

Question 98

Question
______________________ is expresed a a decimal number between -1 to 1, which is know as the correlation coeficient
Answer
  • Correlation
  • Regression
  • A/B testing

Question 99

Question
Correlation +1
Answer
  • Suggest that there is a strong positive relationship between the two variables
  • suggests that there is no relationship at between two variables
  • Suggest that there is a strong negative relationship between the two variables (hipotesis)

Question 100

Question
0 Correlation
Answer
  • Suggest that there is a strong positive relationship between the two variables
  • suggests that there is no relationship at between two variables
  • Suggest that there is a strong negative relationship between the two variables (hipotesis)

Question 101

Question
-1 Correlation
Answer
  • Suggest that there is a strong negative relationship between the two variables (hipotesis)
  • suggests that there is no relationship at between two variables
  • Suggest that there is a strong positive relationship between the two variables

Question 102

Question
sample: "Do students who perform well at elementary school perform equally well at high school"
Answer
  • regression
  • Correlation
  • A/B testin

Question 103

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explores how a dependent variable is related to an independent variable within a dataset
Answer
  • Correlation
  • Regression
  • A/B Testing

Question 104

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Helpss determine how the value od dependent variable changes in relation to changes in the value of the independent varible
Answer
  • Correlation
  • Regression
  • A/B testing

Question 105

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what the analysts discover is that 15% of additional stock in required for enery 5-degree increase in temperature
Answer
  • regression
  • correlation
  • A/b testing

Question 106

Question
more than one independent variable can be tested at the same time
Answer
  • A/B testing
  • Regression
  • correlation

Question 107

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in such cases only one independent variable may change. The others are kept constants
Answer
  • A/B testing
  • Correlation
  • Regression

Question 108

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can help enable a better understanding of what a phenomenin is and why it ocurred
Answer
  • Correlation
  • Regression
  • A/B testing

Question 109

Question
represents a constant rate of change
Answer
  • linear regression
  • Non-linear regression

Question 110

Question
Represents the variable rate of change
Answer
  • linear regression
  • non-linear regression

Question 111

Question
what will be the grades of a student studying at a high school based on her primary school grades
Answer
  • correlation
  • regression
  • A/B testing

Question 112

Question
_________________does not imply a causation. The change in the value of one variable may not be responsible for the change in the value of the second variable. although both may change at the same rate
Answer
  • A/B testing
  • correlation
  • Regression

Question 113

Question
assumes that both variables are independent
Answer
  • Regression
  • correlation
  • A/B testing

Question 114

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Deals with already identified dependent and independent variables
Answer
  • Correlation
  • Regression
  • A/B Testing

Question 115

Question
_________________ can be applied to further explore the relationship and predict the values of the dependent variable, based on the know values of the independent variable
Answer
  • correlation
  • Regression
  • A/B testing

Question 116

Question
is a form of data analysis that involves the graphic representation of data to enable or enhace its visual perception
Answer
  • statistical analysis
  • visual analysis
  • semantic analysis

Question 117

Question
develop a deeper understanding of the data being analyzed. Specifically, it helps identify and highlight hidden patterns, correlations and anomalies.
Answer
  • statistical analysis
  • visual analysis
  • semantic analysis

Question 118

Question
visual analysis
Answer
  • Heat maps
  • time series analysis
  • outlier detectition
  • network analysis
  • spatial data analysis

Question 119

Question
Are an effective visual analysis technique for expressing patterns, data compositions via part-whole relations and geographic distribution of data
Answer
  • time series analysis
  • heat maps
  • spatial data analysis

Question 120

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They also facilitate the identification of areas of interest ans the discovery of extreme (high/low) values wihin a dataset
Answer
  • Network analysis
  • heat maps
  • spatial data analysis

Question 121

Question
___________ itself is a visual, color-coded representation of data values
Answer
  • network analysis
  • heat-maps
  • spatial data analysis
  • time series analysis

Question 122

Question
A _______________ can be in the form of a chart or a map, as shown in the following pages
Answer
  • heat maps
  • time series analysis
  • network analysis
  • spatial data analysis

Question 123

Question
A___________ represents a matrix of values in which each cell is color-coded according to the value
Answer
  • chart
  • map

Question 124

Question
A ___________ represents a geographic measure by wich different regions are color-code according to certain theme
Answer
  • chart
  • map

Question 125

Question
How can i visually identify any patterns related to carbon emission across a large number of cities around the world
Answer
  • Heat maps
  • time series analysis
  • network analysis
  • spatial data analysis

Question 126

Question
____________is the analysis of data that is recorded over periodic intervals of time
Answer
  • heat maps
  • time series analysis
  • network analysis
  • spatial data analysis

Question 127

Question
Helps to uncover patterns within data that are time-dependent. Once identified, the patterns can be axtrapollated for future predictions
Answer
  • heat maps
  • time series analysis
  • network analysis
  • spatial data analysis

Question 128

Question
time series analyses are usually used for forecasting by identifiying long-term trends. seasonal periodic patterns and irregular short-term variations in the dataset
Answer
  • time series analysis
  • heat map
  • network analysis
  • spatial data analysis

Question 129

Question
always includes time as a comparision variable
Answer
  • network analysis
  • heat maps
  • time series analysis
  • spatial data analysis

Question 130

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is generally expressed using a line chart, with time plotted on the x-axis and the recorded data values plotted on the y-axis
Answer
  • time series analysis
  • heat map
  • network analysis
  • spatial data analysis

Question 131

Question
how much yield should the farmer expect based on historical yield data
Answer
  • network analysis
  • spatial data analysis
  • heat maps
  • time series analysis

Question 132

Question
is an interconected collection of entities
Answer
  • heat maps
  • time series analysis
  • network analysis
  • spatial data analysis

Question 133

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An entity can be a person a group or some other business domain object such as a product
Answer
  • spatial data analysis
  • heat maps
  • time series analysis
  • network analysis

Question 134

Question
some conectios may only be one-way, so that transversal in the reverse direction is nor possible
Answer
  • true
  • false

Question 135

Question
is a techniquethat focuses on analizing relationships between entities within the network
Answer
  • time series analysis
  • heat maps
  • network analysis
  • spatial Data analysis

Question 136

Question
There are specialized variations of network analysis
Answer
  • Graphs
  • route optimization
  • social network analysis
  • spread predictions

Question 137

Question
is used to find the shortest routes between the central warehouse and remote stores in order to minimize the durations of deliveries
Answer
  • heat map
  • network analysis
  • spatial data analysis
  • time series analysis

Question 138

Question
How can identify interaction patterns among a very large number of protein-to-protein interactiona?
Answer
  • spatial data analysis
  • network analysis
  • heat maps
  • time series analysis

Question 139

Question
is focused on analizing location-based data in order to find different geographic relationships and patterns between entities
Answer
  • network analysis
  • spatial data analysis
  • time series analysis
  • Heat maps

Question 140

Question
____________________________ is manipulated through a geographical information system (Gis) that plots spatial data on a map generally using its longitude and latitude coordinates
Answer
  • Spatial data
  • structured data
  • unstructured data

Question 141

Question
no two stores can be within a distance of 5 kilometers of each other to prevent the stores from competing with each other.
Answer
  • time series analysis
  • network analysis
  • heat map
  • spatial data analysis

Question 142

Question
how far do customers have to commute in order to get to a supermartket?
Answer
  • spatial data analysis
  • heat maps
  • time series analysis
  • network analysis

Question 143

Question
if the human knowledge can be combined with the processing speed of machines, machines will be able to process large amounts of data without requiring much human intervention
Answer
  • statisctical analysis
  • visual nalysis
  • machine learning
  • semantic analysis

Question 144

Question
machine learning
Answer
  • classification
  • time series analysis
  • clustering
  • outlier detection
  • filtering

Question 145

Question
Two fundamental laws that pertain to machine learning
Answer
  • law of large numbers
  • law commutative
  • Law of dimishing marginal utility

Question 146

Question
the law _____________________________states that the confidence with wich predictions can be made increases as the size of data that is being analyzed increases
Answer
  • law of large numbers
  • law of dimishing marginal utility

Question 147

Question
in other words the accuracy and applicability of the patterns and relationshipsthat are found in a large dataset will be higher that of a smaller dataset
Answer
  • True
  • False

Question 148

Question
the greater the amount of data available for analysis, the better we become of making correct decisions
Answer
  • True
  • False

Question 149

Question
in the context of traditional data analysis, ___________________________ states that, starting with a reasonably large sample size, the value obtained from the analysis of additional data decreases as more data is successively added to the original sample
Answer
  • the law of diminishing marginal utility
  • the law of large number

Question 150

Question
The law of dimishing marginal utility does not apply to big data
Answer
  • True
  • False

Question 151

Question
The greater the volume and variety of data that Big Data solutions can process allows for each additional batch of data to carry greater potential of unearthing new patterns and anomalies. Therefore, the value of each additional batch does not diminish value: rather, it provides more value
Answer
  • True
  • False

Question 152

Question
is a supervised learning technique by witch data is classified into relevant, previously learned categories
Answer
  • classification
  • clustering
  • outlier detection
  • filtering

Question 153

Question
Step 1: The system is fed data that is already categorized or labeled, so that it can develop an understanding of different categories
Answer
  • clustering
  • classification
  • filtering
  • outlier detection

Question 154

Question
step 2: The system is fed unknow (but similar) data for classification, based on the understanding it developed
Answer
  • classification
  • filtering
  • outlier detection
  • clustering

Question 155

Question
A common application of this techniques is for the filtering of e-mail spam. Note that classification can be performed for two or more categories
Answer
  • filtering
  • clustering
  • classification
  • outlier detection

Question 156

Question
Based on old data, a training dataset is compiled that contains tagged examples of customers that have or not previously defaulted
Answer
  • clustering
  • filtering
  • classification
  • outlier detection

Question 157

Question
Does a fingerprint belong to a suspect based on a record of this previous fingerprints
Answer
  • outlier detection
  • clustering
  • classification
  • filtering

Question 158

Question
Is an unsupervised learning technique by wich data is divided into different groups so that the data in each group has similar properties
Answer
  • classification
  • clustering
  • outlier detection
  • filtering

Question 159

Question
There is no prior learning of categories required: instead categories are implicity generated based on the data groupings
Answer
  • outlier detection
  • clustering
  • filtering
  • classification

Question 160

Question
Is generally used in data minig to get an understanding of properties of a given dataset. Afterdeveloping this understanding, classificatioin can be used to make better predictions about similar, but new or unseen data
Answer
  • classification
  • clustering
  • outlier detection
  • filtering

Question 161

Question
In a bank each group is the introduced to one or more financial products most suitable to the characteristics of the overall profile of the group
Answer
  • clustering
  • filtering
  • outlier detection
  • classification

Question 162

Question
How many different categories of elements are there in the periodic table
Answer
  • classification
  • clustering
  • outlier detection
  • filtering

Question 163

Question
Detection is the process of finding data that is significantly different from or inconsistent with the rest of the data within a given dataset
Answer
  • filtering
  • calssification
  • clustering
  • outlier detection

Question 164

Question
this machine learning tecnique is used to identify anomalies, abnormalities and deviations that can be opportunities or risks
Answer
  • outlier detection
  • classification
  • clustering
  • filtering

Question 165

Question
it can be bsaed on either supervised or unsupervised learning
Answer
  • clustering
  • outlier detection
  • classification
  • filtering

Question 166

Question
include fraud detection, medical diagnosis, network data analysis and sensor data analysis
Answer
  • filtering
  • outlier detection
  • classification
  • clustering

Question 167

Question
In order ti find if a transaction is likely to be fraudulent or not, the bank´s IT team builds a sustem emplying ____________________ technique that is based on supervised learning
Answer
  • classificaction
  • clustering
  • outlier detection
  • filtering

Question 168

Question
are there any wrongly identified fruits and vegetables in the training dataset used for classification task
Answer
  • classification
  • outlier detection
  • clustering
  • filtering

Question 169

Question
is the automated process of finding relevant items from a pool of items
Answer
  • classification
  • clustering
  • outlier detection
  • filtering

Question 170

Question
items can be filtered either based on a users own behavior or by matching the behavior of multiple users
Answer
  • classification
  • clustering
  • outlier detection
  • filtering

Question 171

Question
_________________ is generally applied viat the following two approaches
Answer
  • collaborative filtering
  • user behavior
  • content-based filtering

Question 172

Question
items can be filtered either based on a users own behavior or by matching the behavior of multiple users
Answer
  • clustering
  • filtering
  • classification
  • outlier detection

Question 173

Question
A common medium by wich ________________is implemented is via the use of a recomender system
Answer
  • classification
  • clustering
  • outlier detection
  • filtering

Question 174

Question
technique based on the collaboration of users past behavior
Answer
  • collaborative filtering
  • classification
  • clustering
  • outlier detection
  • content-based filtering

Question 175

Question
based on the similarityof users behavior, items are filtered for the target user
Answer
  • classification
  • clustering
  • outlier detection
  • filtering

Question 176

Question
is solely based on the similarity between users behavior, and requires a large amount of user behavior data in order to accurately
Answer
  • filtering
  • classification
  • clustering
  • outlier detection
  • filtering collaborative

Question 177

Question
collaborative filtering is an example of application of law of large numbers
Answer
  • True
  • False

Question 178

Question
technique focused on the similarity between users an items
Answer
  • classification
  • clustering
  • outlier detection
  • filtering
  • content-based filtering

Question 179

Question
A user profile is created based on the users past behavior (likes, ratings, purchase history, etc)
Answer
  • collaborative filtering
  • content_based filtering

Question 180

Question
Contrary to collaborative filtering, content-based filtering is solely dedicated to individual user preferences and does not require data about other users
Answer
  • True
  • False

Question 181

Question
A recomender system predicts user preferences and generate suggestions for the user accordingly
Answer
  • filtering
  • classification
  • clustering
  • outlier detection

Question 182

Question
suggestions commonly pertain to recomending items, such as movies, books, web pages, people etc
Answer
  • clustering
  • classification
  • filtering
  • outlier dtection

Question 183

Question
A recomender system typically uses either collaborative filtering or content-based filtering to generate suggestions
Answer
  • True
  • False

Question 184

Question
recommender system may also be based on a hybrid of both collaborative filtering and content-based filtering to fine-tune the accuracy and effectiveness of generated suggestions
Answer
  • True
  • False

Question 185

Question
Based on matches found between financial product purchased by customers and the properties of similar financial products, the recommnder system automates seggestion for potential financial products that customers may also be interested in
Answer
  • clustering
  • classification
  • filtering
  • outlier detection

Question 186

Question
Wich holiday destinations can be recommended based on the travel history of a holiday makes?
Answer
  • clustering
  • classification
  • outlier detetcion
  • filtering

Question 187

Question
A fragment of text or speech data can carry different meanings in different contexts, whereas a complete sentence may retain its meaning, even if structured in different ways. In order for the machines to extract valuable information, text and speech data needs to be understood by the machines in the same way as humans do. Semantic analysis represents practices for extracting meaningful information from textual and speech data
Answer
  • statistical analysis
  • semantic analysis
  • visual analysis
  • machinne learning

Question 188

Question
types of semantic analysis
Answer
  • natural language processing
  • human behavior language
  • text analytics
  • sentimental analysis

Question 189

Question
Is a computers ability to comprehend human speech and text as naturally understood by humans
Answer
  • text analytics
  • Natural language Processing
  • sentiment analysis

Question 190

Question
This allows computers to perfom a variety of useful task, such as full-text searches
Answer
  • Text analysis
  • sentiment analysis
  • Natural language processiing (NLP)

Question 191

Question
instead of hard-coding the required learning rules, either supervised or unsupervised machine learning is applied to develop the computer undestanding of the natural language
Answer
  • text analysis
  • natural language processing
  • sentiment analysis

Question 192

Question
in general the more learning data the computer has, the more correctly it can decipher human text and speech
Answer
  • natural language Processing
  • text analytics
  • sentiment analysis

Question 193

Question
Natural language processing includes both text and speech recognition
Answer
  • True
  • False

Question 194

Question
For speech recognition the system attempts to comprehend the speech and then performs an action, such as transcribing text
Answer
  • text analytics
  • sentiment analysis
  • Natural language processing

Question 195

Question
How can grammatical mistakes be automaticalle identified?
Answer
  • text analytics
  • Natural Language processing
  • sentiment analysis

Question 196

Question
Unstructured text is generally much more difficult to analyze and search, compared to structured text
Answer
  • True
  • False

Question 197

Question
is the specialized analysis of text through the application of data mining, machine learning and natural language processing techniques to extract value out of unstructured text. Text analytics essentially provides the ability to discover text rather than just search it
Answer
  • Natural language processing
  • text analytics
  • sentimente analysis

Question 198

Question
useful insights from text-based data can be gained by helping business develop an understanding of the information that is contained within a large body of text
Answer
  • True
  • False

Question 199

Question
the basic tenet of text analytics is to turn unstructured text into data that can be searched and analyzed
Answer
  • Natural language processing
  • text analytics
  • sentiment analysis

Question 200

Question
As the amount of digitized documents, e-mail, social media posts and log files increases, businesses have an increasing need to leverage any value that can be extracted from these forms of semi-structured and unstructured data
Answer
  • text analytics
  • natural language processing
  • sentiment analysis
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