Smarter Data Science

CHAPTER 9Constructing for the Long-Term

“A design that doesn't take change into account risks major redesign in the future.”

—Erich Gamma

Design Patterns: Elements of Reusable Object-Oriented Software

The metaphor surrounding the Ladder to AI involves a progressive climb to hone one's skills. But its real purpose is to ensure that artificial intelligence (AI) projects are not tackled tactically and independently as a relentless series of one-off enablements. For decades, IT shops have tried to undo the effects of siloed, standalone applications and databases: those applications that are not integrated—or readily integrated or even capable of integration—with other IT systems. The disintegration often places a burden on the enterprise in terms of cost and addressing new business requirements.

If data and AI efforts are tactically defined and deployed as independent efforts, they are likely to become disenfranchised and fractured. They will ultimately serve to place another IT burden on the enterprise. The Ladder to AI is ultimately a journey for technical continuity: driving sustainable business benefits from AI for short-term gains and long-term utility.

This chapter addresses a number of issues that can inhibit the long-term viability of an information architecture and AI. The goal is to help you achieve a program of smarter data science that can sustainably support mission-critical processes over time. An information architecture must promote across the enterprise full ...