Learn about the key differences between multi-dimensional modeling and relational modeling in analytical systems. Understand if multi-dimensional is a relational concept or not.
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The Lakehouse approach is gaining momentum, but there are still areas where Lake-based systems need to catch up. Databricks have just launched Databricks SQL Analytics, which provides a rich, interactive workspace for SQL users to query data, build visualisations and interact with the Lakehouse platform.
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Everyone’s talking about Azure Synapse Analytics, but does it sometimes feel like they’re talking about different things? Are you having trouble following where Azure SQL Datawarehouse is these days? In this post, Simon attempts to clarify the marketing message and talk about what’s actually coming and where we should be thinking about using it.
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Dake Lakehouse? Another bit of meaningless hype or a new term for a future generation of analytics platforms? I’ll explain the concept and where it’s coming from, and you can decide
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With the term Data Engineer growing exponentially, it can be difficult to pin down what exactly the role is, and where did it come from? This post dissects the history of the data engineer, how it relates to data science and business intelligence and asks the question… is it more than just ETL?
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The ETL window is part and parcel of how BI developers build their solutions - but is it an outdated concept? With event-driven processes, it’s fairly straight forward to move past this as a concept!
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Kimball warehouses have been around for an age, but technology has changed massively since they were designed. So why are people still using it? Does it have a purpose? This blog discusses some of the background behind the questioning of Kimball
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Datawarehousing is a slow, unreactive thing, and it’s missing out on many opportunities because of it. How do you structure your modern data warehouse to react quickly and unlock value within your data, faster?
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