Читать книгу Enterprise AI For Dummies - Zachary Jarvinen - Страница 79

Of the three pillars of AI — processing power, scalable storage, and big data — the third is the one that presents the biggest challenge. How to get it, how to validate it, how to process it.

Figure 3-5 shows the pyramid of critical success factors for AI and analytics. Four of the six layers relate to data, focusing on relevance, accessibility, usability, completeness, and data-based conclusions.

FIGURE 3-5: Pyramid of critical success factors for AI and analytics.

Table 3-2 describes critical questions to answer at each layer.

TABLE 3-2 Pyramid of Critical Success Factors for AI and Analytics

Element	Questions
AI	How will you address analytical deployment, governance, and operations?
Experimentation ML	Does machine learning add business value? How do you define success?
BI / Analytics	What is the story your data is telling? What conclusions can you make from this information?
Explore and Enrich	Can the data be used meaningfully? Are you missing any data or features?
Data Access	Is the data accessible and usable (analysis-ready)? Is the data flow reliable?
Data Collection	Do you have data relevant to your business goals?