Index
Uma Gupta
(Director of Business Analytics, University of South Carolina at Upstate)
San Cannon
(Associate Vice Provost for Data Governance and Chief Data Officer, University of Rochester)
A Practitioner's Guide to Data Governance
ISBN: 978-1-78973-570-3, eISBN: 978-1-78973-567-3
Publication date: 8 July 2020
This content is currently only available as a PDF
Citation
Gupta, U. and Cannon, S. (2020), "Index", A Practitioner's Guide to Data Governance, Emerald Publishing Limited, Leeds, pp. 237-240. https://doi.org/10.1108/978-1-78973-567-320201012
Publisher
:Emerald Publishing Limited
Copyright © 2020 Emerald Publishing Limited
INDEX
Accessibility
, 90
Action plan
, 41
Adaptability
, 28
Adhocracy
, 29–30
Align data strategy
, 79–81
Big data management frameworks
analytics
, 118–119
data sources
, 118
decision-making
, 119
Business-driven data strategy
, 77–79
Business strategy
, 79–81
Capability maturity model (CMM)
, 157
Change management
, 15, 219
data governance
, 35
definition
, 34
Clan culture
, 29
Common language
, 62–63
Communications
, 13, 43, 91–92
agreement
, 54–55
common language
, 62–63
context
, 50–52
definitions
, 49–50
describing data
, 58–60
documentation
, 55–56
emotions
, 57–58
foundational work
, 48–49
inform vs. persuade
, 65–67
language
, 58
oral vs. written
, 64–65
people
, 61–62
politics
, 56–57
push vs. pull
, 63–64
repeat vs. reiterate
, 67–68
standards
, 52–54
Culture
, 14–15, 189–191, 219
Data collection
, 135–137
Data control
, 8
Data-driven culture
, 41–44
Data ethics
, 133–135
Data governance
big data management frameworks
, 117–121
case studies
, 167–185, 187–216
change management
, 15
changes
, 11
chief data officer
, 106–108
cloud computing framework
, 116–117
communications
, 13
culture
, 14–15
data control
, 8
data-related problems
, 8–9
definition
, 3–7, 218
elements
, 11–13
frameworks
, 101–122
hard skills
, 9
institutional data
, 110–113
investment
, 2–3
mainstream resources
, 2
organizational placement
, 108–110
research
, 1, 2, 110–113
responsibility
, 15–17
soft skills
, 9
structure
, 103–106
Data Governance Office (DGO)
, 200–207
Data literacy
, 129–132
Data management capability model (DCAM)
, 158–161
Data management maturity (DMM)
, 157–158
Data quality
, 91
accuracy
, 125
assessment frameworks
, 127–128
completeness
, 125
consistency
, 125
data cleansing
, 126
high quality
, 126–127
timeliness
, 125
uniqueness
, 125
Data-related problems
, 8–9
Data transformation
, 192
Defensive strategy
, 85–88
Describing data
, 58–60
Disengaged C-suite
, 95
Documentation
, 55–56
Electronic health record (EHR)
, 189
Emotions
, 57–58
Enterprise data warehouse (EDW)
, 191, 193–194
Ethics
, 133–135
analytics
, 140–141
data collection
, 135–137
data sharing
, 137–140
European General Data Protection Regulation (GDPR)
, 136
External relationships
, 27
Facilities Inventory Classification Manual
, 50
Foundational work, communication
, 48–49
Hard skills
, 9
Hierarchy-oriented culture
, 30
HIMSS Analytics Adoption Model for Analytics Maturity
, 199–200
HIPPO management
, 56
Incentives
, 40
Insights
, 148–149
Integration
, 146–147
Integrity
, 147–148
Internal maintenance
, 27
IT-driven data strategy
, 77–79
Key performance indicator (KPI)
, 80–81
Known quality
, 126
Language
, 58
Literacy
, 129–132
Market-oriented culture
, 30
Maturity models
capability maturity model (CMM)
, 157
caution
, 152–154
comparative
, 151–152
data assessment
, 145–146
data insights
, 148–149
data integration
, 146–147
data integrity
, 147–148
data management capability model (DCAM)
, 158–161
data management maturity (DMM)
, 157–158
definition
, 156
descriptive
, 149–150
generic steps
, 144–145
IBM maturity model
, 162–164
levels
, 154–156
predictive
, 150
prescriptive
, 150
Mechanistic processes
, 27
Mission
, 28
Offensive strategy
, 85–88
O-foods
, 82–83
Operational data store (ODS)
, 194
Organic processes
, 27
Organization
, 11, 188–189
Organizational culture
adaptability
, 28
adhocracy
, 29–30
clan culture
, 29
cultural models
, 26
hierarchy-oriented
, 30
involvement
, 28
market-oriented
, 30
mission
, 28
multidimensional aspects
, 26–27
person culture
, 31–32
power culture
, 30–31
role culture
, 31
standard organizational behavior
, 22
task culture
, 31
types
, 36
values
, 29
Ownership
, 90
Person culture
, 31
Politics
, 56–57
Power culture
, 30–31
Responsibilities
, 92–93
Role culture
, 31
Statistical literacy
, 130
Strategy, data
accessibility
, 90
align data strategy
, 79–81
blame-game
, 94
business-driven data strategy
, 77–79
business strategy
, 79–81
communications
, 91–92
conflict
, 94
cost
, 90
customers
, 93–94
data quality
, 91
disengaged C-suite
, 95
examples
, 81–82
integrity
, 91
IT-driven data strategy
, 77–79
key performance indicator (KPI)
, 80–81
offensive vs. defensive strategy
, 85–88
O-foods
, 82–83
organizations
, 73
ownership
, 90
quality
, 89
quantity
, 89
responsibilities
, 92–93
risks
, 90–91, 95
roles
, 92–93
source of data
, 89
Task culture
, 31
Tribal loyalties
, 137
Values
, 29
Vision
, 40
- Prelims
- 1 Foundations of Data Governance
- 2 Impact of Organizational Culture and the Need for Change Management
- 3 Communication: Key to Success
- 4 Data Strategy
- 5 Data Governance Frameworks
- 6 Data Governance Components: Data Quality, Literacy, and Ethics
- 7 Data Governance Maturity Models
- 8 Summary Case Studies
- 9 Detailed Case Study
- 10 Execution Roadmap
- Notes
- Resources and References
- Index