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).
Este curso faz parte do Programa de cursos integrados Database systems
Business intelligence and data warehousing
oferecido por
935 Inscrito
Programa - O que você aprenderá com este curso
Semana
11 hora para concluir
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 vídeos (total de (Total 9 mín.) min), 1 leitura, 1 teste
1 leituras
Welcome to the course10min
1 exercício prático
Business intelligence12min
Semana
23 horas para concluir
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 vídeos (total de (Total 11 mín.) min), 2 testes
1 exercício prático
Designing a Data Warehouse18min
Semana
32 horas para concluir
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 vídeos (total de (Total 6 mín.) min), 2 testes
1 exercício prático
The ETL process and Analytical queries with SQL
Semana
45 horas para concluir
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 vídeos (total de (Total 27 mín.) min), 3 testes
1 exercício prático
Data mining
Semana
515 minutos para concluir
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 vídeos (total de (Total 10 mín.) min), 1 teste
2 videos
Integrate, store and analyze unstructured data5min
1 exercício prático
Types of data
Semana
63 horas para concluir
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 vídeos (total de (Total 17 mín.) min), 3 testes
2 exercícios práticos
Concepts of Big Data and Hadoop Framework40min
Assesment
Instrutores
María del Pilar Ángeles
Full time professor at the Department of Computer EngineeringDepartment of Computer Engineering
Sobre 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.
Sobre o Programa de cursos integrados Database systems
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.
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.
O que recebo ao me inscrever nesta Especialização?
Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.
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