Today’s
post is very short because I decided last month to publish this article
under our new Michelin public blog about IT. This blog post talks about Exponential
Information Systems and Data-Driven Enterprise Architecture. The pitch about Data Strategy, Architecture
and Infrastructure is very similar to what I said in the “Rise
of the Data Cloud” podcast episode that was just released.
To give you a preview, here are some of the ideas that I develop in this article:
- A target data infrastructure must follow the lambda architecture principles and support both data lakes for cold analytics and event-driven data flows for hot analytics.
- Hot analytics is more resilient and agile, thus better suited to crisis situations such as COVID, when models trained with past data are no longer relevant.
- AI and Data Engineering should be embedded into system thinking : there are no obvious quick wins (at least they are very rare) while most successes are built on reinforcing loops. Data, algorithms, usage and business value are co-developed simultaneously and continuously.
- Advanced AI is most often hybrid AI; the most powerful integration paradigm is the “system of intelligent systems” approach.
I encourage
you to visit our Michelin IT blog regularly, we see it as a platform for
continuous learning, to share ideas and a passion for building the next
generation of software systems.
