Data lake concept has evolved a lot recent years. Traditionally, data lake is used interchangeably with Hadoop. In Hadoop data and compute are co-located to reduce data transfer latency, thus improving the performance. However, in Cloud era, data lake concept is dramatically evolved. Nowadays in cloud, compute nodes and data storage are normally decoupled, which brings significant benefit for scalability, cost optimization, upgradability etc. Modern cloud data ecosystem is all built upon this concept. The data lake storage is the foundation for most of the Azure data services, e.g. data factory, databricks, Azure datawarehouse, PowerBI. The concept of common data model enables business application and Azure services to work with same data in Azure data lake storage and makes different roles in organization e.g. data engineer, data scientists, business analysts to work in a much more seamless way.
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