分类目录:Big Data and AI

以下是分类 Big Data and AI 下的所有文章

使用 PolyBase 将数据加载到 Azure SQL 数据仓库

使用 PolyBase 是将大量数据加载到高吞吐量 Azure SQL 数据仓库的有效方法。 使用 PolyBase 而非默认 BULKINSERT 机制可以实现吞吐量的巨大增加。 如果源数据位于 Azure Data Lake Storage Gen2 中,且格式与 PolyBase 兼容,则可使用复制活动直接调用 PolyBase,让 Azure SQL 数据仓库从源拉取数据。 如果 PolyBase 最……

通过数据工厂将数据载入 Azure SQL 数据库的最佳做法

将数据复制到 Azure SQL 数据库时,可能需要不同的写入行为: 追加:我的源数据只包含新记录。 更新插入:我的源数据包含插入和更新内容。 覆盖:我需要每次都重新加载整个维度表。 使用自定义逻辑进行写入:在将数据最终插入目标表之前,我需要额外的处理。 有关如何在 Azure 数据工厂中进行配置和最佳做法,请参阅相……

Data Lake Security – Four Key Areas to Consider When Securing Your Data Lake

Lately, we have been dealing with some new interesting conditions and requirements that involve data lake security. It’s an apparently simple concept. But break it into its two sub-concepts and you would quickly notice plenty of complexity and detail within these three words. On the one hand……

ETL (Extract-Transform-Load)

ETL comes from Data Warehousing and stands for Extract-Transform-Load. ETL covers a process of how the data are loaded from the source system to the data warehouse. Currently, the ETL encompasses a cleaning step as a separate step. The sequence is then Extract-Clean-Transform-Load. Let us briefly ……

ELT vs. ETL

Many organizations are increasingly turning to ELT(Extract, Load, and Transform) tools to address the volume, variety, and velocity of big data sources, which often strain conventional Extract, Transform and Load (ETL) tools designed for internal, relational data warehousing. ELT vs ETL: What’s t……