Part 4/12:
Interoperability: Seamless collaboration between different systems and teams, akin to chefs collaborating in a busy kitchen.
Data Modeling: Perhaps the most crucial component—constructing meaningful representations of data that provide context, especially when integrating both structured and unstructured sources.
Historically, data modeling has been an often-overlooked, yet vital, element. It involves creating logical structures and relationships that transforms raw data into actionable insights. Without robust data modeling, even the most sophisticated AI models may falter.
The Challenge with Traditional Data Modeling
Traditional data modeling faces numerous hurdles, which have become more pronounced with the advent of AI. These include: