Data Science Strategy For Dummies

Index

Numbers

• 1-tool approach, data science pitfall, 37

• 2-sided business model, 272–273

A

• aaS (as a Service), 192, 282
• accelerated processing units (APUs), 225
• acquisition layer, 182
• activities, for data-driven business models, 277–278
• actuating stage, of data science strategy, 17–18
• Acumos, standardization from, 50
• adaptability, 178
• administrative metadata, defined, 88
• AdSense, Google, 270
• advertising (revenue model classification), 279
• advisory services, 229
• aggregated data, maintaining, 13
• agile mindset, 162
• AI. See artificial intelligence (AI)
• AI/ML (artificial intelligence/machine learning) models, 218–221
• algorithm economy, 240
• algorithms
  • AI ethics and, 98, 99
  • being machine driven with, 116–117
  • black box challenge, 46
  • data product categories, 250–251
  • definition of, 203
  • Explainable AI and, 45
  • reproducible results from, 99
• alternative delivery models, 282
• Amazon, example of API delivery model, 290–291
• Amazon Machine Learning (Amazon ML), 221
• AMP lab, standardization from, 50
• analog data, vs. digitized data, 114
• analytics
  • advanced, 15
  • analytics projects, 58–59
    • descriptive analytics, 58
    • diagnostic analytics, 58–59
    • predictive analytics, 59
  • applying to customers, 258–259
  • basic analytics, 15
  • center of excellence (CoE) and, 137
  • data management and, 112
  • difference between reporting and, 14
  • digital twins and, 77
  • objective of, 309
  • as stage of data science strategy, 14–16
  • techniques, 15
• Analytics, Google, 250, 258
• analytics vendors, 183
• Angoss (predictive modeling ...