Choosing the right data model for your healthcare enterprise data warehouse (EDW) is one of the most significant decisions made in establishing a data warehousing and foundational analytics strategy for the future. The right data model can significantly speed up your analytics time-to-value and adaptability, or significantly burden your project with disastrous consequences in agility and project delays.
In the healthcare industry where the data environment is much more complicated than a sales receipt and the analytic uses cases are constantly changing, the Kimball and Inmon approaches can be challenging in their impact on agility and initial time-to-value. This is why a new Late-Binding™ approach to data warehousing is quickly becoming discussed and viewed as an alternative approach to solving healthcare’s unique data challenges.
Join Steve Barlow as he addresses the strengths and weaknesses of each of the following three primary Data Model approaches for data warehousing in healthcare:
Enterprise Data Model
Independent Data Marts
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