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所在平台: Udemy |
课程主页: https://www.udemy.com/course/consume-data-with-power-bi/
课程评论：没有评论
**课程名称：** 设计数据仓库 (Designing a Data Warehouse) **课程概述：** 本课程旨在教授如何设计和构建数据仓库，这是一个能够集中存储、分析信息，从而支持更明智决策的核心系统。数据仓库汇聚了来自交易系统、关系数据库及其他来源的数据，这些数据以定期频率流入。业务分析师、数据工程师、数据科学家和决策者通过商业智能（BI）工具、SQL客户端及其他分析应用来访问这些数据。 在当今竞争激烈的商业环境中，数据和分析已成为不可或缺的要素。业务用户依赖报表、仪表板和分析工具来提取数据洞察、监控业务表现并支持决策。数据仓库通过高效存储数据、最小化数据输入输出（I/O），并能同时为成百上千的用户快速提供查询结果，为这些关键工具提供动力。 数据仓库是专门为数据分析而设计的，它涉及读取大量数据以理解数据间的关系和趋势。而数据库则用于捕获和存储数据，例如记录交易详情。 **课程内容涵盖：** * **维度表 (Dimension Tables) 的设计：** 学习如何设计维度表，这些表在数据仓库的星型模式中存储描述事实表对象的属性或维度。维度是关于可衡量事件的参考信息的集合。 * **数据仓库的物理设计 (Physical Design)：** 指的是使用SQL语句创建数据库的过程。在物理设计阶段，您会将逻辑设计阶段收集的数据转化为物理数据库结构的描述。物理设计决策主要受查询性能和数据库维护方面的考虑驱动。 * **数据仓库的逻辑设计 (Logical Design)：** 逻辑设计过程涉及将数据组织成一系列称为实体 (Entities) 和属性 (Attributes) 的逻辑关系。实体代表一块信息；在关系数据库中，实体通常映射到一个表。属性是实体的组成部分，有助于定义实体的独特性。
A data warehouse is a central repository of information that can be analysed to make more informed decisions. Data flows into a data warehouse from transactional systems, relational databases, and other sources, typically on a regular cadence. Business analysts, data engineers, data scientists, and decision makers access the data through business intelligence (BI) tools, SQL clients, and other analytics applications.Data and analytics have become indispensable to businesses to stay competitive. Business users rely on reports, dashboards, and analytics tools to extract insights from their data, monitor business performance, and support decision making. Data warehouses power these reports, dashboards, and analytics tools by storing data efficiently to minimize the input and output (I/O) of data and deliver query results quickly to hundreds and thousands of users concurrently.A data warehouse is specially designed for data analytics, which involves reading large amounts of data to understand relationships and trends across the data. A database is used to capture and store data, such as recording details of a transaction.This course explains the design of dimension tables, physical and logical design of a data warehouse.Physical design is the creation of the database with SQL statements. During the physical design process, you convert the data gathered during the logical design phase into a description of the physical database structure. Physical design decisions are mainly driven by query performance and database maintenance aspects.The process of logical design involves arranging data into a series of logical relationships called entities and attributes. An entity represents a chunk of information. In relational databases, an entity often maps to a table. An attribute is a component of an entity that helps define the uniqueness of the entity.A dimension table is a table in a star schema of a data warehouse. A dimension table stores attributes, or dimensions, that describe the objects in a fact table. In data warehousing, a dimension is a collection of reference information about a measurable event.
