A set of generic methods and rules to design a sturdy, cost-efficient, and scalable knowledge mannequin on your post-modern knowledge stack.
Over the previous few years, because the Trendy Information Stack (MDS) launched new patterns and requirements for transferring, remodeling, and interacting with knowledge, dimensional knowledge modeling steadily turned a relic of the previous. As an alternative, knowledge groups relied on One-Huge-Tables (OBT) and stacking layer upon layer of dbt fashions to sort out new use instances. Nonetheless, these approaches led to unlucky conditions during which knowledge groups turned a value middle with unscalable processes. So, as we enter a “post-modern” knowledge stack period, outlined by the pursuit to cut back prices, tidy up knowledge platforms, and restrict mannequin sprawl, knowledge modeling is witnessing a resurrection.
This transition places knowledge groups in entrance of a dilemma: ought to we revert again to strict knowledge modeling approaches that had been outlined many years in the past for a very completely different knowledge ecosystem, or can we introduce new rules which can be outlined primarily based on at present’s expertise and enterprise issues?
I consider that, for many firms, the fitting reply lies someplace within the center. On this article, I’ll talk about a set of information modeling requirements to maneuver away from…
