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Carlos Marques
Marketing Manager
Why Big Data
Projects Fail?
Why Big Data
Projects Fail?
DO IT!!by Carlos Marques
#FAILby Carlos Marques
I NEED
A PROJECTby Carlos Marques
Businessby Carlos Marques
TECHNOLOGY
AS A SILVER
BULLET
by Carlos Marques
ONE SIZE
FITS ALLby Carlos Marques
ACCESS
TO DATAby Carlos Marques
DO THINGS
DIFFERENTLYby Carlos Marques
CONNECT
THE DOTS?by Carlos Marques
FAIL CAN
BE GOODby Carlos Marques
DO IT
YOURSELF?by Carlos Marques
TEAMWORKby Carlos Marques
BABY STEPSby Carlos Marques
READY
TO GROW
by Carlos Marques
TOP
MANAGEMENT
SUPPORT?
by Carlos Marques
TOP
MANAGEMENT!!!by Carlos Marques
THE BIG
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by Carlos Marques
SUCCEEDby Carlos Marques
Finco's Talks by Carlos Marques

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Notes de l'éditeur

  1. Mais empresas a tirar valor dos seus dados. Muitas falham.Exemplos com analogia IKEA
  2. Um projecto Big Data é acima acerca de tudo sobre tomar a iniciativa sem medo de atingir resultados… mesmo que negativos.No entanto, 92 % das organizações ainda estão, ou planeiam começar "algum dia " ou evitam grandes projetos que envolvam modelar os dados disponíveis á organização.
  3. Muitas das empresas falham Pelas mesmas razões Falhar rápido e pequeno Quando falha, normalmente as implicações são graves
  4. Definir o projeto é o primeiro passo Estabelecer um cronogramaA criação de metas de projeto e alocação de recursos. Estas medidas irão ajudar a definir o trabalho que precisa ser feito para entregar o projeto no prazo e dentro do orçamento definido.
  5. O sucesso de qualquer programa relacionado com grandes análises de dados deve seralinhado com a equipa que dirige o programa. A no domínio do negócio por parte da equipa responsável pelo projectovai alavancar a modelação dos dados para obter os resultados.
  6. Falham devido aofoco excessivo na tecnologia em vez das necessidades de negócio.IT olhar para a infra-estrutura necessáriaem vez de olhar para os requisitos de negócio para a o business case. Este programa é para o negócio, e é tudo sobre o negócio. Este não é um projeto de IT.
  7. Pensar que trabalhar com casos de sucesso do fornecedor podem-se alcançar ganhos rápidos. As Organizações são únicas,suas interpretações de dados precisam ser olhado a partir dessa perspectiva. Os casos de sucesso devem see adaptados com base no foco que as organizações têm para o futuro.
  8. Maiores desafios é tentar reunir toda a informação que está dispersa nos diversos silos de dados Existem unidades de negócio e funções organizacionais que constituem esses silos de informação e que necessitam de ser ligados para dar sentido á informação (por exemplo, contact center , marketing, vendas ).
  9. Empresas com projetos excessivamente ambiciosos que ainda não estão prontas para endereçar, ou projectos que tentam resolver grandes problemas baseados na modelação de dados,utilizando tecnologias de análise de dados tradicionais. Em ambos os casos, falhar é o resultado habitual.
  10. Big data está disponível em torno de nós em várias formas e tamanhos. Compreender a importância de cada um destes conjuntos de dados para as necessidades de negócios é um aspecto fundamental para ter sucesso.
  11. Não importa o quão inteligente a equipa é na análise de dados.Muito provavelmente as perguntas iniciais vão estar erradas. Provavelmente vão deixar de coletar os dados corretos para obter respostas para as questões. Falhem mas aprendam com os erros.
  12. Projectos param ou falham devido á falta de skills das pessoas envolvidos nos projetos.A restrição das equipas internas, é terem conhecimento limitado e apenas à realidade que conhecem.
  13. Cooperem com parceiros de negócio externos para identificar oportunidades e soluções. O impacto desses projetos também deve ser " grande". Criar uma equipe inter -organização e envolver todas as partes no início do jogo . Protejam sempre talento interno e externo crítico.
  14. Permanecer focado nos grandes volumes de dados durante muito tempo, irá conduzir ao desastreComeçar um projeto pequeno ajuda a trabalhar com riscos identificados onde os passos são claros e seguros.
  15. Estejam prontos para um crescimento rápido. Os projetos podem crescer rapidamente e de forma exponencial. É importante criar um roadmap que permita expandir o conhecimento a outras áreas e capitalizar os sucessos anteriores para ganhar mais apoio dentro da organização.
  16. As oportunidades relacionadas a analise de dados melhoram a receita e aumentam a produtividade… mas também requerem novos talentos e investimentos em infra-estrutura de ITPor isso é melhor mesmo terem o apoio do top management.
  17. É deste top management que falo e não do anterior. Vocês vão passar a chegar um pouco mais tarde a casaVão ser inquiridos se existe uma nova colega gira no trabalho… vocês perceberam o que quero dizer.
  18. A fim de criar mais valor para a empresa, é necessário ter uma visão global dos objetivos da organizaçãoPerceber a organização e a estratégia, permite executar um plano de entrega de valor as varias áreas em diferentes fases. 
  19. Uma das coisas mais surpreendentes sobre aprender a ter sucessoenvolve saber lidar com o fracasso, o que a maioria das pessoas procuram evitar. Se as crianças pequenas desistissem de aprender a andar, só porque caem durante o processo de aprendizagem, onde estaria a raça humana?