Index

Data Science and Analytics

ISBN: 978-1-80043-877-4, eISBN: 978-1-80043-876-7

Publication date: 4 December 2020

This content is currently only available as a PDF

Citation

(2020), "Index", Kumari, S., Tripathy, K.K. and Kumbhar, V. (Ed.) Data Science and Analytics, Emerald Publishing Limited, Bingley, pp. 183-189. https://doi.org/10.1108/978-1-80043-876-720211010

Publisher

:

Emerald Publishing Limited

Copyright © 2021 Emerald Publishing Limited


INDEX

Note: Page numbers followed by “n” indicate notes.

Accuracy
, 58

Additive manufacturing (AM)
, 155, 160

Aggregate measures
, 92–93

Analysis
, 2–3

Analysis of variance (ANOVA)
, 75, 132

Analytics (see also Predictive analytics)
, 8

Analyzer technologies
, 162–164

Anand city
, 75

Anand Milk Union Limited (AMUL)
, 74

Application programming interface (API)
, 44

Artificial Intelligence (AI)
, 3, 152, 160–161

Assembling and natural resources
, 38

Association rule mining
, 109

Autonomous vehicles
, 160

Bar charts
, 11

Basket analysis
, 109–110

Big data (BD)
, 7, 24–25, 152, 159

applications
, 27

average wage paid
, 138–139

basics
, 26–28

comparison of notified wage and agriculture wage
, 144–146

computing
, 26

cumulative number of households issued job cards
, 134

delay payment
, 142

employment demanded vs. employment offered
, 142

gender and women empowerment
, 140–142

ingestion
, 34

meaning
, 28

and MGNREGA
, 131–146

MGNREGA expenditure
, 139

MIS
, 132

number of job cards deleted
, 132

number of registered households and persons
, 133

pre-and post-MGNREGA wage situation
, 146

semi-skilled worker
, 134

system
, 30

trend of activities in MGNREGA
, 134–135

work demand pattern
, 136

Big data analytics (BDA)
, 24, 27

Box plots
, 14–15

Business analytics based on customer data
, 108–110

Business Data Analytics
, 3

Business intelligence (BI)
, 9

Capital
, 118–119

Categorical data
, 10

Challenges in MGNREGA
, 118–119

Charottar (see Anand city)

Classification
, 56–59

Cloud computing (CC)
, 152, 159

Cloudera Distribution including Apache Hadoop (CDH)
, 53

Cluster
, 75

analysis
, 75

Clustering
, 42, 45

algorithms
, 109

Collector technologies
, 162–164

Communication layer
, 113–114

Composite user interface
, 114

Comprehensive R Archive Network (CRAN)
, 48

Confusion matrix
, 58

Counting measures
, 92–93

Cross validation
, 46, 59

Custolytics
, 104

Customer relationship management (CRM)
, 104

business analytics based on customer data
, 108–110

customer life cycle management with real-time data analytics
, 112

IoT architecture
, 112–114

IoT-based real-time analytics
, 110–111

limitations
, 116

theoretical foundation
, 105–108

Customer(s)
, 77

customer-driven businesses
, 104

data analytics
, 110

equity
, 92, 94–95, 99

life cycle management with real-time data analytics
, 112

segmentation
, 108–109

service improvement
, 158, 162

Dashboards
, 16–18

Data (see also Big data (BD))

mining
, 42, 44, 108

science
, 1

traffic analysis
, 92

traffic problems in IoT in context of health-care problems using wireless communication
, 95–96

types
, 9–10

Data visualization
, 2, 7, 9

future
, 21

software
, 18–21

Database marketing
, 109

Datasets
, 56

Decision-making
, 1–2, 16

DeenDayal Upadhyaya Antyodaya Yojana–NRLM (DAY-NRLM)
, 124

DeenDayal Upadhyaya Gramin Kaushal Yojana (DDU-GKY)
, 124

Descriptive analytics
, 8

Digital champion
, 154–157

Digital supply chain (DSC) (see also Supply chain)
, 153

Digital technologies
, 105, 116, 152

benefits
, 162–164

effects
, 161–165

implementing
, 153–159

strategic implementation
, 157–159

in supply chain
, 159–161

Digitalization
, 152, 154–155

Drone
, 160

Dwarkadhish tea, market segmentations of
, 83–86

Education
, 38

Electronic CRM (eCRM)
, 105–108

Employment
, 118

programs
, 123–124

Employment Assurance Scheme (EAS)
, 124–125

Employment Guarantee Act
, 122

Enterprise Resource Planning systems
, 2

Entrepreneurs
, 90

Entrepreneurship
, 90

Event orchestration engine
, 114

Event-driven architecture
, 113–114

Event-driven service-oriented architecture (EDSOA)
, 112

benefits
, 114

Extreme poverty
, 118

Feature extraction
, 46–47

Financial data management
, 37

Food For Works Program (FFP)
, 124–125

Food retail market
, 73

Food Safety Standard Authority of India Act (FSSAI Act)
, 72, 89

Forecasting
, 10, 13

Foreign direct investment (FDI)
, 72, 89

Future research of MGNREGA
, 149–150

Gen-next customer service
, 111

General Public License (GPL)
, 47

Global Positioning System (GPS)
, 161

Golden Jubilee Rural Self-Employment Program
, 124

Goods and services tax (GST)
, 72, 90

Google Maps
, 3–4

Government
, 39

Gram Panchayat
, 131n1

Gram Sabha (GS)
, 131

Graph
, 11

Graphical processing unit (GPU)
, 25

Graphical user interface (GUI)
, 44

Graphical visualizations
, 11–18

Hard core loyal
, 90

Heat map
, 8, 13

Heterogeneous, Autonomous, Complex, Evolving hypothesis (HACE hypothesis)
, 29

High-performance computer clusters (HPCCs)
, 29

Higher-order functions of densities
, 97

Histogram
, 12–13

Horizontal collaborator
, 154

Hortonworks Data Platform (HDP)
, 53

Household enterprises
, 123

IBM predictive analytics tools
, 44

Income generation
, 123

Indian agriculture
, 73

Indiastat
, 3

Information and communications technology (ICT)
, 147, 152

Information technology
, 110

Institute of Rural Management (IRMA)
, 74

Insurance firms
, 38

Integrated development environment (IDE)
, 49

Integrated Rural Development Program (IRDP)
, 123–124

Integration Services
, 31

International Water Management Institute (IWMI)
, 75

Internet of Things (IoT)
, 24, 104, 110, 152, 159

architecture
, 112–114

IoT-based real-time analytics
, 110–111

Interpreter technologies
, 164–165

Interval data
, 10

IT security
, 114

Jawahar Gram Samridhi Yojana (JGSY)
, 124–125

Jawahar Rozgar Yojana (JRY)
, 124–125

K-fold method
, 59

K-Nearest Neighbor (K-NN)
, 56

Karnavati Dabeli, market segmentations of
, 81–83

Khetlaaapa tea, market segmentation of customers for
, 81

Knowledge, skill, and aptitude (KSA)
, 89

Konstanz Information Miner (KNIME)
, 44, 49–51, 56, 61, 65

Labor employment
, 118–119

Liberalization, Privatization, and Globalization (LPG)
, 89

Likert scale
, 10

Line charts
, 15

Machine learning
, 42, 46–47

Magic Quadrant
, 18

Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA)
, 119

Big Data and
, 131–146

implementation mechanism
, 125–126

issues and challenges in
, 146–148

literature review
, 120–124

physical and financial implementation status
, 126–131

research methodology
, 119

research questions
, 149–150

salient features
, 128, 131

theoretical and managerial implications
, 149

trend of activities in
, 134–135

wage employment programs
, 124–125

Management Information System (MIS)
, 132

Manufacturing time
, 153, 156

Market basket analysis (see Association rule mining)

“Market Opportunities through Effective Market Analytics”
, 74

area of study
, 74–75

justification of research methodology
, 76

materials and methods
, 74–76

sample selection and design
, 75

statistical tools and techniques
, 75–76

Market segmentation

of consumer market of Nylon Pauvaji restaurants
, 79–80

of consumer market of Sigdi restaurant
, 76–78

of customers for Khetlaaapa tea
, 81

of Dwarkadhish tea
, 83–86

of Karnavati Dabeli
, 81–83

of Santushti ice-cream parlor
, 86–88

Marketing
, 92

campaigns targeted toward
, 109

Mean
, 15

Measurements
, 10

Media information exchange and entertainment
, 37–38

Median
, 15

Messaging bus
, 113

Micro small and medium enterprises (MSMEs)
, 115–116

Micro Strategy
, 19

Microsoft’s Power BI
, 19

Modern CRM
, 114–115

Multimedia
, 25

Multimedia big data (MMBD) (see also Big data (BD))
, 25

applications
, 36–37

basic advantages
, 36

features
, 32–33

importance
, 34–36

infrastructure
, 28–29

life cycle
, 33–34

meaning
, 32

open problems outlook and research opportunities
, 37–39

related work in BD computing
, 29–31

Multimodality
, 25

Multivariate analysis of variance (MANOVA)
, 76

“MyFord Touch” service
, 158

Naïve Bayes Classifier
, 58

National Association of Software and Services Companies (NASSCOM)
, 3

National Dairy Development Board (NDDB)
, 74

National Highway (NH)
, 76

National Rural Employment Guarantee Act (NREGA)
, 125

National Rural Livelihood Mission (NRLM)
, 124

National Sample Survey Organization (NSSO)
, 120

Node
, 50

Nominal data
, 9

Non-resident Indian city (NRI city)
, 75

North American Council of Transportation Efficiency (NACFE)
, 160

Nylon Pauvaji restaurants, market segmentation of consumer market of
, 79–80

Object Management Services (OMS)
, 31

On-demand pricing
, 111

One-way ANOVA test
, 139

Open data
, 6–7

Orange
, 44, 51–52, 56, 61

Ordinal data
, 10

Organizations
, 44

Percentage-split method
, 59

Performance measures of modeling
, 93

Persistence Services
, 31

Personal digital assistants (PDAs)
, 26

Pie chart
, 12

“Platoon” concept
, 160

Poverty
, 118

alleviation
, 123

in India
, 120–122

Prediction
, 58

Predictive analysis
, 42

used in decision-making
, 43

Predictive analytics
, 8, 42–43

analysis
, 66

background details
, 45–54

classification
, 56–59

datasets
, 56

evaluating performance of algorithms
, 59–66

experiment setups and preliminaries
, 59

methodology
, 54–59

objective
, 45

selection of tools
, 54, 56

Predictive models
, 42

Prescriptive analytics
, 8

Product density (PD)
, 92, 94, 96–99

of second-order
, 98

Promotional marketing
, 111

Psychographic segmentation
, 73

Python
, 19, 21

QlikView
, 19

Qualitative data
, 10

Quality
, 73

Quality of service (QoS)
, 92

Quantitative data
, 10

R software
, 19, 21, 44

Radio-frequency identification (RFID)
, 112

Random point process (RPP)
, 92, 94–95, 100

Random process
, 100

Random variables
, 94

RapidMiner
, 44, 53–54, 56, 66–67

RapidMiner Radoop
, 53

RapidMiner Server
, 53

RapidMiner Streams
, 53

RapidMiner Studio
, 53

Ratio data
, 10

Real-time data analytics, customer life cycle management with
, 112

Recency, frequency and monetary value framework (RFM framework)
, 109

Regression
, 42, 45

Retailing
, 72

Robotics (Rob)
, 160

RStudio
, 48–49, 61

Rural development
, 118

Rural employment
, 123

Rural Employment Guarantee Schemes (REGS)
, 121–122

Rural Landless Employment Guarantee Program (RLEGP)
, 124–125

SampoornGramin Rozgar Yojana (SGRY)
, 124–125

Santushti ice-cream parlor, market segmentations of
, 86–88

Scatter plot
, 13

Scheduled caste (SC)
, 135

Scheduled tribe (ST)
, 135

Scikit-learn
, 44–47, 61

Seamless integration
, 113

Second-order product density
, 98–99

Segmentation
, 89

Self-driving vehicles (SDV)
, 160

Self-employment
, 123

Sensing layer
, 113

Service-oriented architecture (SOA)
, 113

Sigdi restaurant, market segmentation of consumer market of
, 76–78

Spider chart
, 15

Split cases
, 75–76

Standard operating procedure (SOP)
, 73, 90

Stereoscopic 3D video
, 35

Stochastic modeling, appropriateness of technique in
, 94–95

Stochastic point process
, 92–93

data traffic problems in IoT in context of health-care problems
, 95–96

expected cost of resources
, 99

prediction of expected number of patients undergoing treatment
, 96–99

Stochastic time-dependent modeling of customer equity
, 99

estimating customer base of product
, 100–101

estimating customer equity at any time
, 101

Supervised learning algorithms
, 46

Supply chain
, 152

digital technologies in
, 159–161

management
, 156–157

Supply Chain Operations Reference model (SCOR model)
, 157

Support Vector Classifier (SVC)
, 58

Support Vector Machine (SVM)
, 45

System of records (SOR)
, 114

Tableau
, 19

Tanagra
, 44

Technology

costs
, 109

implementation
, 155–156

Test dataset
, 56

Thoughtspot
, 19

Three dimensional printing (3D printing) (see Additive manufacturing (AM))

Training dataset
, 56

Transformer technologies
, 164–165

Transportation
, 39

Tree map
, 13

UI Services
, 31

Uncertainty
, 152

Unemployment
, 118

in India
, 120–122

Unique selling propositions (USPs)
, 19, 86

Unmanned aerial vehicle (UAV)
, 160

Unsupervised learning algorithms
, 46

Variety, velocity, value, volume, veracity, and variability (six Vs)
, 32

VisFlow
, 21

Visual merchandising
, 89

Visualization
, 7–8

types
, 10–18

Visualization and Data Analytics lab (VIDA lab)
, 21

Volume, Velocity, and Variety (three Vs)
, 27

Wage

employment programs
, 124–125

goals
, 118–119

good
, 118–119

Waikato Environment for Knowledge Analysis (WEKA)
, 44, 47–48, 56, 59–61

Whisker plots
, 14–15

Word clouds
, 15–16

Worker population ratio (WPR)
, 122

Workflow
, 50

Yet Another Learning Environment (YALE)
, 53

Zomato vertical model
, 73–74