Informações sobre o curso: 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).
Para quem é direcionado este curso: A learner with previous database systems experience will be able to design, test, and implement analytical, transactional or NoSQL database systems according to business requirements by programming reliable, scalable and maintainable applications and resources using SQL and Hadoop ecosystem. By the end of this Specialization, learners will have completed 4 progressively harder database projects.
Desenvolvido por: Universidade Nacional Autônoma do México
Ministrado por: María del Pilar Ángeles, Full time professor at the Department of Computer Engineering
Department of Computer Engineering
| Informações básicas | Curso 2 de 4 no Database systems Specialization |
| Nível | Intermediário |
| Idioma | Inglês |
| Requisitos de hardware | Window o Linux. You will need: 8-10 GB of RAM and 500 GB de HDD. |
| Como ser aprovado | Seja aprovado em todas as tarefas para concluir o curso. |
Programa
SEMANA 1
Introduction 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 videos, 1 leituras, 1 testes para praticar
- Reading: Welcome to the course
- Discussion Prompt: Welcome!
- Vídeo: How data is analyzed?
- 练习测验: Business intelligence
SEMANA 2
Designing 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 videos, 1 testes para praticar
- Vídeo: Steps to Multidimensional model OLTP
- Discussion Prompt: Business intelligence project
- 练习测验: Designing a Data Warehouse
Nota atribuída: OLAP Bookstore Requirements
SEMANA 3
The 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 videos, 1 testes para praticar
- Vídeo: Typical OLAP operations
- 练习测验: The ETL process and Analytical queries with SQL
- Discussion Prompt: The ETL process
Nota atribuída: Bookstore Analytical Queries
SEMANA 4
Predictive 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 videos, 1 testes para praticar
- Vídeo: ID3 Algorithms
- 同学互评: Formative Exercises
- Discussion Prompt: Predictive Analytics with Data mining
- 练习测验: Data mining
Nota atribuída: Bookstore Data Mining Queries
SEMANA 5
The problem of integration and analysis of unstructured data
After completing this module, a learner will learn the types of data according to structure and how to integrate, store and analyze unstructured data.
2 videos, 1 testes para praticar
- Vídeo: Integrate, store and analyze unstructured data
- 练习测验: Types of data
- Discussion Prompt: Unstructured data
SEMANA 6
Big Data and Hadoop Framework
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.
2 videos, 1 testes para praticar
- Vídeo: Analysis of unstructured data
- 练习测验: Concepts of Big Data and Hadoop Framework
- Discussion Prompt: Analysis of data
- 同学互评: Labs Hadoop
Nota atribuída: Assesment
Perguntas frequentes
Como funciona
课程作业
每门课程都像是一本互动的教科书，具有预先录制的视频、测验和项目。
来自同学的帮助
与其他成千上万的学生相联系，对想法进行辩论，讨论课程材料，并寻求帮助来掌握概念。
证书
获得正式认证的作业，并与朋友、同事和雇主分享您的成功。
Desenvolvedores
Universidade Nacional Autônoma do México
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.
Custo
| Comprar curso | |
|---|---|
| Acesso aos materiais do curso | Disponível |
| Acesso a materiais valendo nota | Disponível |
| Receba uma nota final | Disponível |
| Obtenha um Certificado de Curso compartilhável | Disponível |
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