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Building a Data Lakehouse with Azure Synapse
How to build a modern Data Platform in the Microsoft Cloud
A Data Lakehouse is a modern architecture that combines Data Lake and Data Warehouse. In the Azure Cloud there are several possibilities to build such a Data Lakehouse — one of them is the use of Azure Synapse.
What is Azure Synapse?
Microsoft Azure Synapse Analytics is the successor to Azure SQL Data Warehouse. With the new service, Microsoft wants to expand its modern Data Warehouse and Big Data strategy and enables companies to analyze their data more effectively and faster. To dive deeper into this topic and what the strenghts of Azure Synpse are you can use this article:
What is a Data Lakehouse (Recap)?
Let’s briefly explain what a Data Warehouse is, for those who are not yet familiar with the subject. A Data Lakehouse is not just about integrating a Data Lake with a Data Warehouse, but rather integrating a Data Lake, a Data Warehouse, and purpose-built storage to enable unified governance and ease of data movement [1]. From my own experience, it has often shown that a Data Lakes can be realized much faster. Once all data is available, Data Warehouses can still be built on top of it as a hybrid solution. Read more about it here.
How to use Azure Synpase for a Data Lakehouse
The services required for building a Data Lakehouse are all available in Azure for the time being and are well integrated with each other. Here, you can use Data Factory to handle your data integration from various sources — be it structured, semi-structured or completely unstructured data. Of course, you can also use platform-independent tools like Alteryx or Talend, but if you’re already in the Azure cloud, Data Factory may make…
