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).
提供方
教学大纲 - 您将从这门课程中学到什么
周
1Introduction to Business Intelligence as Analytical System
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!
2 个视频 （总计 9 分钟）, 1 个阅读材料, 1 个测验
1 个阅读材料
Welcome to the course10分钟
1 个练习
Business intelligence12分钟
周
2Designing a Data Warehouse
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.
2 个视频 （总计 11 分钟）, 2 个测验
1 个练习
Designing a Data Warehouse18分钟
周
3The ETL process and Analytical queries with SQL
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.
2 个视频 （总计 6 分钟）, 2 个测验
1 个练习
The ETL process and Analytical queries with SQL
周
4Predictive Analytics with Data mining
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.
2 个视频 （总计 27 分钟）, 3 个测验
1 个练习
Data mining
讲师
María del Pilar Ángeles
Full time professor at the Department of Computer EngineeringDepartment of Computer Engineering
关于 墨西哥国立自治大学
La Universidad Nacional Autónoma de México fue fundada el 21 de septiembre de 1551 con el nombre de la Real y Pontificia Universidad de México. Es la más grande e importante universidad de México e Iberoamérica. Tiene como propósito primordial estar al servicio del país y de la humanidad, formar profesionistas útiles a la sociedad, organizar y realizar investigaciones, principalmente acerca de las condiciones y problemas nacionales, y extender con la mayor amplitud posible, los beneficios de la cultura.
关于 Database systems 专项课程
This specialized program is aimed at computer people who want to enter the field of information systems and learn their different types of requirements, architectures, performance, techniques and tools so you can know when to use business intelligence, data mining, data science, databases , databases in memory or big data in order to have reliable, maintainable and scalable data intensive systems. Through 4 courses, you will cover [transactional relational databases, business intelligence and Data warehousing, NoSQL technologies, and reliable, scalable and maintainable data intensive applications that will prepare you for a specialized information system consultant or data scientist.
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