Page 119 - The Real Work Of Data Science Turning Data Into Information, Better Decisions, And Stronger Organizations by Ron S. Kenett, Thomas C. Redman (z-lib.org)_Neat

112 Index

context maturity levels, 77
of car, data, 68 organization structure affects, 73
of organizational ecosystem, 2 outputs of, 95–96
and soft data, 21–23 to perform impact analysis, 41–42
control chart, 78, 79 real work of, 87
cost performance index (CPI), 15 recent technical advances in, 99–100
Courtney Smith, 29 team, 26
Cox, Sir David, 87 wide‐angle perspective of, 39
CPI see cost performance index (CPI) data scientists, 5, 6, 14, 21, 22, 23, 25, 26, 29, 31,
craft activities, 83 33, 35, 37, 40, 45, 55
customer, understanding the real problem, 17–19 building a network of, 74–76
car analogy, 70
data, 55, 89 decisions, 49
companies management approach and analytic employed at an international semiconductor
capabilities, maturity level of, 77–81 company, 73
dealing with immediate issues, 27–29 ethical considerations and today’s, 113–114
defined, 93–94 harvest data from social media, 80
educating senior leaders, 67–71 implications for, 85
hard, 35 important for, 44
soft, 35 integrated data from wafer production
tomorrow’s quality issues, 29–30 line, 78
trustworthiness, 28 life of, 57
untrustworthy, 25–27 reality steps, 38
data analysis, 88 real problem, understanding, 17–19
data analytics rigged decisions, 50
life‐cycle view of, 2–5 skills of, 91–92
maturity curve, 79 starter kit of questions, 59–60
“data and information lens,” 15 treat second‐guessing, 46
data collection, 3, 22 “data sharing,” 16
data‐driven, 6, 43, 69 data space, 69
Antis, traits of, 46 car analogy, 70
companies and people, 43–44 data visualization, 34
traits of, 44–45 Davenport, Tom, 1
data governance, 69 decision‐maker, 18, 19, 27, 31–35, 37, 43,
data lab, 75 50, 59
data lens, 15–16 decision‐making, root out bias in, 49–53
data models, 93 demanding decision‐maker, 55
data monetization, 70 Deming, W. Edwards, 21, 73–75, 84, 88
data protection, 97 digital transformation, 69
data quality, 28, 71 digitization, 69
results, 32 directed imagination, 70
statistics, 25–27 domain expert ecosystem, 19
tomorrow’s issues, 29–30 domain experts, 22
data science, 35, 55, 74, 89 "domain‐specific generalization," 35
assessing information quality, 63–64 Doumont, Jean‐Luc, 34
“center of excellence,” 75
educating senior leaders, 67–71 The Economic Control of Quality of
in every sector, 74–75 Manufactured Product (Shewhart), 88
hands‐on information quality workshop, 64–66 Einstein, Albert, 18
industrial revolutions and, 83–86 elements of PSE, 39–41