Index

admiral and the consigliere, 126

agile methods, 119–20

architecting data, 95

Åsman, Michael, 48

business data, 111

harmonizing, 48–49

business data design

and governance, 149

Business Data Design arena, 52, 54, 57, 110, 113

and data governance lead, 143

and responsibility, 68

cooperation, 142–48

decisions, 148–53

successful, 72–78

business data model

as a diplomat tool, 200

business data modeling workshop, 186–88

facilitator and, 189

business data models, 170, 208

advantages of, 202–4

and accountability, 157–60

and business requirements, 202–4

real-world experience and, 205–8

requirement work for, 170

business domain data architects, 140–42

business event data, 88, 91–92

business expectations, 56

business processes

managing, 160–62

category data, 87, 89–90

change

be the, 181–83

why needed, 178

commercial off the shelf (COTS) application, 172

concept and feasibility studies, 169–70

construction, 213–14

construction section, 215

content management management

and diplomacy, 103–4

COTS, 80, 172, 207

data

common, 94–101

decisions about, 162–64

employee, 46–47

kinds of, 84–94

sharing, 94

data accuracy, responsibility for, 157–60

data architects, 142

and data governance, 40

and entity managers, 147

data areas, map of, 133

data centralization, 99

data consistency, 144

data content, 101–9

Data Content arena, 52, 102

and real-life cases, 104–6

organizing, 153–64

data content management, 102

principles of, 106–9

data design, 57

responsibility for, 67–72

Data Design arena

organizing, 134–38

data design models, 196

data design standardization, 99

data diplomacy, 20–21

and truth in data, 40–45

examples of, 26–49

data diplomacy approach, 15

data diplomacy mode, 24–25

data diplomat, 20–21, 24–25

arenas of, 51

as intermediaries, 112

data disparation, 99

data governance, 13–15

and assigning roles, 177

and bureaucracy, 106

and data stewards, 155–56

and diplomacy, 17–20, 21–23, 51–55, 175–77

and the IT areana, 116

drivers for, 14

for master data, 160–62

four arenas of, 51–55

framework, 15

principles of, 22

the entirety of, 58–67

traditional, 19

data governance arenas, 122, 175

data governance entirety arena, 51, 58–67

and decision-making, 62–63

and management system, 64

and proactivity, 61

and staffing, 60–61

and work growth, 63

meaning of, 125

organizing the, 125–48

data governance frameworks, 121

setting up, 183–86

data governance lead, 150, 165, 168

funding of, 128–30

in the Business Data Design arena, 143

role of, 126–28

data governance management system, 64

data governance maturity

and Volvo Penta, 26

data governance program

of Volvo Penta, 30–32

data governance structure

roles in, 122–24

data governance work

the nature of, 63

data improvement work, 61

data lifetime, 86–94

data management

expectations on, 55–58

data managers, 16

data migration, 173

data model in a workshop, 192

data model story, 208–18, 213–16

data modeling workshop

pitfalls, 193–96

data models, 157, 159, 160

as storytelling, 208–18

story example, 213–16

storytelling, 216–18

use of, 154

data negotiation model, 101

Data Processing arena, 57, 110–20

organizing, 164–74

data processing solutions arena, 52

data quality management, 102

data quality rates, 102

data responsibilities, 158

data steward, 155–56

data types, 86, 93

data unification, 100–101

data worker, 15–16

decision preparation process, steps in, 151

detail operational data, 88, 92

diplomacy

and data governance, 17–20

diplomacy ingredients, 45

diplomatic approach

and discrepancies, 32–36

diplomatic workshop

hints, 196–200

employee data

and data governance, 46–47

Enterprise Architecture Made Simple, 168

enterprise data architect, 165

role of, 130–31

enterprise data architect, diplomatic, 131–34

enterprise data architecture, 131–34

enterprise data model, 65–67, 131

purposes of, 65–66

entity accountable, 138–39

entity managers, 135–38, 145, 149, 152

as subject experts, 165

facilitator, 199

preparation and the, 189–90

fact-based business requirements, 200–204

fields of challenges, 98

Fischer, Sofie, 48

five running guys, the, 218–24

gravity, 29–30

in-house built systems, 171

IT activities and processes

how to improve, 165–70

IT arena

and data diplomacy, 116–19

roles in, 124

IT processes

benefits of, 113

IT systems, dissatisfaction with, 111

and diplomacy, 114–15

lifestyle characteristics, 87

Lindholm, Johan, 49, 164

Lindroth, Lena, 28, 30

location address, 215–16

maintenance work, 174

managerial arena

roles in, 123–24

metadata governance

vs data governance, 57

mindsets, different

benefits and challenges of, 218

model story contents, 210–12

operational arena

roles in, 124

opportunity, using an, 37–39

parties, kinds of, 96

pre-launch work, 173–74

project initiation, 168

Project portfolio, planning, 166–68

regulatory requirements, 55

requirement work, 170

resource data, 87, 90–91

responsibility, 123

results, study, 181

Ross’s operating model, 98

Sales Order business data model, 90

Salo-Premmert, Jonny, 27, 29, 30

shared data

definitions, 94–101

Silverston, Len, 210

situation, revealing the, 178–80

systems acquisitions, 172

UML (Unified Modeling Language), 196

unshared data, 97

Volvo Penta

and data diplomacy, 26–32

data governance program of, 30–32

workshop

business data modeling, 186–88

business data modeling, pitfalls, 193–96

execution and, 190–93

steps contain in, 191