Explore the strategic importance of evolving data relationships and their impact on data-driven insights in our latest blog post. Learn how shifts in business rules require significant re-engineering, affecting data management and decision-making. Essential reading for executives and business analysts, this discussion highlights the need for adaptable data practices to maintain competitive advantage in a…
Embracing Many-to-Many Relationships in Data Modeling: A Technical Guide PREFACE: there is another false belief out there: Many-to-many (links, pits, bridges) are bad and lead to join hell, and should never be used. WRONG…. want to know why? read on. Note: anyone who claims “LINKS ARE BAD” or “MANY-TO-MANY should never be used” needs to
Too many consultancies provide the following advice: Model your data warehouse with source system relationships, maintain source system referential integrity. In this article we will explore why: a) this is really bad advice, and b) leads to a rigid data warehouse requiring re-engineering when loading a new source. If you want to build a data
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Explore the strategic importance of evolving data relationships and their impact on data-driven insights in our latest blog post. Learn how shifts in business rules require significant re-engineering, affecting data management and decision-making. Essential reading for executives and business analysts, this discussion highlights the need for adaptable data practices to maintain competitive advantage in a dynamic business environment.
Embracing Many-to-Many Relationships in Data Modeling: A Technical Guide PREFACE: there is another false belief out there: Many-to-many (links, pits, bridges) are bad and lead to join hell, and should never be used. WRONG…. want to know why? read on. Note: anyone who claims “LINKS ARE BAD” or “MANY-TO-MANY should never be used” needs to…
Too many consultancies provide the following advice: Model your data warehouse with source system relationships, maintain source system referential integrity. In this article we will explore why: a) this is really bad advice, and b) leads to a rigid data warehouse requiring re-engineering when loading a new source. If you want to build a data…