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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-modeling-for-olap-datawarehouses/
课程评论：没有评论
Coursera课程《系统设计-数据仓库/OLAP数据库数据建模》深入探讨了数据仓库数据建模与传统主数据库模式设计的根本差异。 该课程强调，数据仓库的核心目标是支持对海量记录进行聚合查询，这类查询成本高昂，但查询频率远低于面向消费者的主数据库。因此，数据仓库采用截然不同的数据布局和索引模型，这类数据库被称为OLAP数据库。 课程将带领学员深入了解OLAP数据库的内部架构，重点关注查询在OLAP数据库中的运行机制。学员将学习OLAP数据库提供的各类优化查询的手段，并通过实际案例学习如何为数据仓库中的OLAP数据库设计数据模型。 课程以AWS Redshift作为OLAP数据库的示例，同时指出其中涵盖的原则具有通用性，可广泛应用于Snowflake、Hive等数据仓库，甚至部分适用于HBase等实时列式存储数据库。
Designing a data model for a data warehouse is fundamentally different from designing the schema for your primary database. A data warehouse is meant for supporting aggregation queries that touch a huge number of records and are very expensive. The scale in terms of number of queries is at least an order of magnitude less than the number of queries seen by a consumer-facing primary database. This distinction leads to a fundamental different data layout and indexing model in the database used in a data warehouse. Such databases are called OLAP databases.This course will take you into the internal architecture of an OLAP database with specific focus on areas that help you how a query runs on an OLAP database. We will walk though the levers that an OLAP database provides to optimize your queries. We will then cover various scenarios that will help you design the data model for an OLAP database used in a data warehouse.Throughout this course, we will use AWS Redshift as the OLAP database. However, the principles covered in this course are general and can be applied in any data warehouse including Snowflake or Hive. Some of these principles are also applicable in real-time column stores like HBase.
