Welcome to part two of our Teradata performance optimization series. In this article, we will delve into how a good data model can prevent future performance issues in data warehousing projects. We will also discuss the drawbacks of taking over operational systems’ source definitions directly and the importance of surrogate keys. Stay tuned for part three on fixing a broken data model.
Avoid data warehouse project failures by choosing the right data model. In this article, we explore denormalization techniques for when it makes sense, including repeating groups, prejoins, and derived information. We also discuss alternatives to denormalization, such as Global Temporary Tables and Volatile Tables. Remember, denormalization can improve performance but has significant drawbacks and should be used only when necessary.
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