After an organization has collected its data and organized it in a trusted, unified view, it can tap into that data to build and scale AI models across the business. This allows companies to glean insights from all of their data, no matter where it resides, and engage with AI to transform their business—putting themselves at a clear competitive advantage.
The earlier rungs on the AI Ladder were about getting ready to make usable models based on reliable data. Now, on the Analyze rung (Figure 8-1), we can actually put that data to work and bring AI and machine learning into the picture. This is where we move from theory to practice; where the rubber meets the road, so to speak.
Figure 8-1. The Analyze rung of the AI Ladder
This rung of the AI Ladder presents its own unique challenges. Hasty investments at this stage can create some serious issues with regard to tools, people, and processes. Point solutions create complexity in integration, maintenance, and support, leading to increased technical challenges and costs. And there is the whole issue of ensuring trust and explainability for the analytical models built on this rung. A failure on this front can make your entire AI investment worth nothing, because nobody believes the results are worth using.
In this chapter, we’ll discuss the process of analyzing your data and building your analytics capability. ...
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