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DATA WAREHOUSE Cassius Busemeyer Cristiane Luquetta Rafael Slonik
1º computador em 1946
Armazenamento de dados Anos 60
Dispositivo de armazenamento Acesso direto (DASD) Anos 70
Linguagem 4ª geração Computador pessoal Anos 80 - 90
OLTP gerou SAD que  por sua vez gerou DW
DW é orientado por temas,
É integrado, DW é orientado por temas,
Não-volátil e É integrado, DW é orientado por temas,
Variante no tempo Não-volátil e É integrado, DW é orientado por temas,
 
OLAP: (Online Analytical Processing) OLTP: (Online Transaction Processing) <ul><li>Do negócio; </li></ul><ul><li>Transacio...
 
Como funciona o data warehouse ?   Metadados : “dados sobre dados”; Granularidade : nível de detalhe contido nas unidades ...
Data Mart é um DW segmentado, por departamento, por exemplo
 
Método Kimball
Método Inmon
O data warehouse é o ponto central de todos os seus dados ; O sistema Linux suporta o processamento de extração, transform...
Data Mining Mineração de dados
“ Data mining  é o processo de busca de dados por  padrões  anteriormente desconhecidos e uso freqüente destes padrões par...
Simplificando...
Torture  os dados até eles confessarem ... Se você torturar o suficiente, eles irão confessar tudo - ACM SIGKDD
 
O  Web Mining  apresenta-se como responsável pela procura de  regras e padrões  importantes de uma forma automática. Permi...
<ul><li>Compreender o domínio da aplicação, entender as expectativas do usuário final do processo. </li></ul><ul><li>2. Cr...
4. Transformar (reduzir e reprojetar) os dados (encontrar atributos úteis e interessantes). 5. Escolher a tarefa, métodos,...
<ul><li>Aprendizagem Supervisionada: </li></ul><ul><ul><li>Classificação ( Árvores  e Regras). </li></ul></ul><ul><li>Apre...
Caso de  Fracasso Gazelle.com (simulado) : CL/DM caro Total Information Awareness : ético?
Cases de  Sucesso IMS América: campanha de MKT Harrah’s Entertainment Inc : clientes prospects Highmark: fraudes
Créditos pelas fotos: Sxc.hu e Flickr.com Referências no próximo slide Obrigado! Cassius Busemeyer  - cassiusbusemeyer@hot...
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Data warehouse & Data mining

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Apresentação sobre Data warehouse e Data mining do curso de Gestão da Informação UFPR. Matéria Informática aplicada II (Business Intelligence).

Autores: Cassius Busemeyer, Cristiane Aparecida Luquetta, Rafael Slonik

Publié dans : Technologie
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  • DOWNLOAD THIS BOOKS INTO AVAILABLE FORMAT (2019 Update) ......................................................................................................................... ......................................................................................................................... Download Full PDF EBOOK here { https://urlzs.com/UABbn } ......................................................................................................................... Download Full EPUB Ebook here { https://urlzs.com/UABbn } ......................................................................................................................... Download Full doc Ebook here { https://urlzs.com/UABbn } ......................................................................................................................... Download PDF EBOOK here { https://urlzs.com/UABbn } ......................................................................................................................... Download EPUB Ebook here { https://urlzs.com/UABbn } ......................................................................................................................... Download doc Ebook here { https://urlzs.com/UABbn } ......................................................................................................................... ......................................................................................................................... ................................................................................................................................... eBook is an electronic version of a traditional print book THIS can be read by using a personal computer or by using an eBook reader. (An eBook reader can be a software application for use on a computer such as Microsoft's free Reader application, or a book-sized computer THIS is used solely as a reading device such as Nuvomedia's Rocket eBook.) Users can purchase an eBook on diskette or CD, but the most popular method of getting an eBook is to purchase a downloadable file of the eBook (or other reading material) from a Web site (such as Barnes and Noble) to be read from the user's computer or reading device. Generally, an eBook can be downloaded in five minutes or less ......................................................................................................................... .............. Browse by Genre Available eBooks .............................................................................................................................. Art, Biography, Business, Chick Lit, Children's, Christian, Classics, Comics, Contemporary, Cookbooks, Manga, Memoir, Music, Mystery, Non Fiction, Paranormal, Philosophy, Poetry, Psychology, Religion, Romance, Science, Science Fiction, Self Help, Suspense, Spirituality, Sports, Thriller, Travel, Young Adult, Crime, Ebooks, Fantasy, Fiction, Graphic Novels, Historical Fiction, History, Horror, Humor And Comedy, ......................................................................................................................... ......................................................................................................................... .....BEST SELLER FOR EBOOK RECOMMEND............................................................. ......................................................................................................................... Blowout: Corrupted Democracy, Rogue State Russia, and the Richest, Most Destructive Industry on Earth,-- The Ride of a Lifetime: Lessons Learned from 15 Years as CEO of the Walt Disney Company,-- Call Sign Chaos: Learning to Lead,-- StrengthsFinder 2.0,-- Stillness Is the Key,-- She Said: Breaking the Sexual Harassment Story THIS Helped Ignite a Movement,-- Atomic Habits: An Easy &amp; Proven Way to Build Good Habits &amp; Break Bad Ones,-- Everything Is Figureoutable,-- What It Takes: Lessons in the Pursuit of Excellence,-- Rich Dad Poor Dad: What the Rich Teach Their Kids About Money THIS the Poor and Middle Class Do Not!,-- The Total Money Makeover: Classic Edition: A Proven Plan for Financial Fitness,-- Shut Up and Listen!: Hard Business Truths THIS Will Help You Succeed, ......................................................................................................................... .........................................................................................................................
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Data warehouse & Data mining

  1. 1. DATA WAREHOUSE Cassius Busemeyer Cristiane Luquetta Rafael Slonik
  2. 2. 1º computador em 1946
  3. 3. Armazenamento de dados Anos 60
  4. 4. Dispositivo de armazenamento Acesso direto (DASD) Anos 70
  5. 5. Linguagem 4ª geração Computador pessoal Anos 80 - 90
  6. 6. OLTP gerou SAD que por sua vez gerou DW
  7. 7. DW é orientado por temas,
  8. 8. É integrado, DW é orientado por temas,
  9. 9. Não-volátil e É integrado, DW é orientado por temas,
  10. 10. Variante no tempo Não-volátil e É integrado, DW é orientado por temas,
  11. 12. OLAP: (Online Analytical Processing) OLTP: (Online Transaction Processing) <ul><li>Do negócio; </li></ul><ul><li>Transacional; </li></ul><ul><li>Operacional; </li></ul><ul><li>Volátil; </li></ul><ul><li>Não-padronizada; </li></ul><ul><li>Sobre o negócio; </li></ul><ul><li>Analítica: </li></ul><ul><li>Tático-estratégica; </li></ul><ul><li>Não-volátil; </li></ul><ul><li>Padronizada; </li></ul><ul><ul><li>Outros: </li></ul></ul><ul><ul><li>ROLAP (relacional); </li></ul></ul><ul><ul><li>MOLAP (Multi); </li></ul></ul><ul><ul><li>HOLAP (Híbrido); </li></ul></ul><ul><ul><li>DOLAP (Desktop); </li></ul></ul>
  12. 14. Como funciona o data warehouse ? Metadados : “dados sobre dados”; Granularidade : nível de detalhe contido nas unidades de dados existentes no data warehouse; ETL :Extrair,Transformar,Carregar (Vidotti,2001)
  13. 15. Data Mart é um DW segmentado, por departamento, por exemplo
  14. 17. Método Kimball
  15. 18. Método Inmon
  16. 19. O data warehouse é o ponto central de todos os seus dados ; O sistema Linux suporta o processamento de extração, transformação e carregamento e suporta também a Interface do Usuário; O tempo de trabalho foi reduzido de fato em 20%
  17. 20. Data Mining Mineração de dados
  18. 21. “ Data mining é o processo de busca de dados por padrões anteriormente desconhecidos e uso freqüente destes padrões para predizer conseqüências futuras.” - Jeff Jonas e Jim Harper
  19. 22. Simplificando...
  20. 23. Torture os dados até eles confessarem ... Se você torturar o suficiente, eles irão confessar tudo - ACM SIGKDD
  21. 25. O Web Mining apresenta-se como responsável pela procura de regras e padrões importantes de uma forma automática. Permite saber, por exemplo, quais os padrões de navegação típicos dentro do site, o que caracteriza os visitantes / clientes ou qual a sua propensão para adquirir determinado produto ou serviço . Fonte: http://www.novabase.pt/showNews.asp?idProd=reswebmining
  22. 26. <ul><li>Compreender o domínio da aplicação, entender as expectativas do usuário final do processo. </li></ul><ul><li>2. Criar/selecionar uma coleção de dados para aplicação. </li></ul><ul><li>3. Pré-processar e limpar os dados (eliminar impurezas e dados irrelevantes). </li></ul>O Processo de KDD
  23. 27. 4. Transformar (reduzir e reprojetar) os dados (encontrar atributos úteis e interessantes). 5. Escolher a tarefa, métodos, modelos, parâmetros etc. do processo de mineração de dados e executar este processo. 6. Interpretar os resultados. 7. Consolidar o conhecimento adquirido, resolver conflitos.
  24. 28. <ul><li>Aprendizagem Supervisionada: </li></ul><ul><ul><li>Classificação ( Árvores e Regras). </li></ul></ul><ul><li>Aprendizagem Não-super-visionada : </li></ul><ul><ul><li>Associação; </li></ul></ul><ul><ul><li>Clustering. </li></ul></ul>Mineração de Dados
  25. 29. Caso de Fracasso Gazelle.com (simulado) : CL/DM caro Total Information Awareness : ético?
  26. 30. Cases de Sucesso IMS América: campanha de MKT Harrah’s Entertainment Inc : clientes prospects Highmark: fraudes
  27. 31. Créditos pelas fotos: Sxc.hu e Flickr.com Referências no próximo slide Obrigado! Cassius Busemeyer - cassiusbusemeyer@hotmail.com Cristiane Luquetta - criscrical@hotmail.com Rafael Slonik – rafael@novo-mundo.org

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