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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/business-intelligence-data-warehousing
课程评论：没有评论
课程名称：商业智能与数据仓库 课程概述：欢迎参加商业智能与数据仓库的专项课程。本课程为期六周，通过视频和各种文档，帮助您轻松学习如何识别、设计和开发分析信息系统，如商业智能和数据仓库的描述性分析。您将能够理解高容量非结构化数据（大数据）的集成和预测分析问题，以及数据挖掘和Hadoop框架。 完成本课程后，学习者将能够： - 创建基于分析业务需求和OLTP系统的星型或雪花数据模型图。 - 创建物理数据库系统。 - 将数据提取、转换并加载到数据仓库中。 - 使用MySQL编写分析查询。 - 使用RapidMiner进行预测分析。 - 将关系型或非结构化数据加载到Hortonworks HDFS。 - 执行Map-Reduce作业以查询HDFS上的数据以进行分析。 编程语言：本课程将使用MySQL语言。 需下载软件： - RapidMiner - MySQL - Excel - Hortonworks Hadoop框架 如果您使用的是Mac或iOS操作系统，则需要使用虚拟机（VirtualBox或VMware）。 课程大纲： 1. 第一部分：商业智能作为分析系统的介绍 - 该模块介绍数据仓库的步骤，以自动化企业所需的分析过程。 2. 第二部分：设计数据仓库 - 学习者将能够识别数据仓库的全过程，包括OLAP设计概念和多维建模。 3. 第三部分：ETL过程与SQL分析查询 - 学习者将区分结构化和非结构化数据，并能够将数据提取、转换并加载到数据仓库中。 4. 第四部分：数据挖掘的预测分析 - 该模块介绍主要的数据挖掘任务及其分类、回归和聚类算法。 5. 第五部分：非结构化数据的集成与分析问题 - 学习者将了解数据的结构类型以及如何集成、存储和分析非结构化数据。 6. 第六部分：大数据与Hadoop框架 - 该模块解释大数据的问题及Hadoop生态系统的解决方案，可以在特定条件下应用该生态系统的各个组成部分。
Part: 1
Title:Introduction to Business Intelligence as Analytical System
Description:In the first module named Introduction to Business Intelligence as Analytical System, we will learn how the steps of the process of datawarehousing to automate analytical processes that companies need for their business strategies. Let's start!
Part: 2
Title:Designing a Data Warehouse
Description:After completing this module, a learner will be able to identify the entire process of datawarehousing, which consist on OLAP design concepts and multidimensional modelling. The learner will be able to design and create a data warehouse from OLAP requirements.
Part: 3
Title:The ETL process and Analytical queries with SQL
Description:After completing this module, a learner will differentiate from structured and unstructured data and will be able to extract, transform and load data into a datawarehouse. The student will also be able to program and execute OLAP queries with SQL.
Part: 4
Title: Predictive Analytics with Data mining
Description:After completing this module, a learner will identify the main data mining tasks and some algorithms for classification, regression and clustering for predictive and descriptive analysis on business intelligence.
Part: 5
Title:The problem of integration and analysis of unstructured data
Description:After completing this module, a learner will learn the types of data according to structure and how to integrate, store and analyze unstructured data.
Part: 6
Title:Big Data and Hadoop Framework
Description:After completing this module, a learner will understand the problem of big data, a possible solution to the analysis of big data with the Hadoop ecosystem and under which conditions should be apply each element of this ecosystem.
Welcome to the specialization course Business Intelligence and Data Warehousing. This course will be completed on six weeks, it will be supported with videos and various documents that will allow you to learn in a very simple way how to identify, design and develop analytical information systems, such as Business Intelligence with a descriptive analysis on data warehouses. You will be able to understand the problem of integration and predictive analysis of high volume of unstructured data (big data) with data mining and the Hadoop framework. After completing this course, a learner will be able to ● Create a Star o Snowflake data model Diagram through the Multidimensional Design from analytical business requirements and OLTP system ● Create a physical database system ● Extract, Transform and load data to a data-warehouse. ● Program analytical queries with SQL using MySQL ● Predictive analysis with RapidMiner ● Load relational or unstructured data to Hortonworks HDFS ● Execute Map-Reduce jobs to query data on HDFS for analytical purposes Programming languages: For course 2 you will use the MYSQL language. Software to download: Rapidminer MYSQL Excel Hortonworks Hadoop framework In case you have a Mac / IOS operating system you will need to use a virtual Machine (VirtualBox, Vmware).
