March 2025
Intermediate to advanced
278 pages
8h 22m
Portuguese (Portugal, Brazil)
Content preview from Decifrar as arquitecturas de dados
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
Capítulo 5. Lago de dados
Este trabalho foi traduzido com recurso a IA. Agradecemos o teu feedback e comentários: translation-feedback@oreilly.com
Os grandes volumes de dados começaram a surgir em volumes sem precedentes no início da década de 2010 devido a um aumento das fontes que produzem dados semi-estruturados e não estruturados, tais como sensores, vídeos e redes sociais. Os dados semi-estruturados e não estruturados possuem uma quantidade fenomenal de valor - pensa nas informações contidas em anos de e-mails de clientes! No entanto, na altura, os armazéns de dados relacionais só conseguiam lidar com dados estruturados. Também tinham dificuldade em lidar com grandes quantidades de dados ou dados que precisavam de ser ingeridos frequentemente, pelo que não eram uma opção para armazenar estes tipos de dados. Isto obrigou a indústria a encontrar uma solução: os lagos de dados. Os lagos de dados podem lidar facilmente com dados semi-estruturados e não estruturados e gerir dados que são ingeridos com frequência.
Há alguns anos, falei com analistas de uma grande cadeia de retalho que queriam ingerir dados do Twitter para ver o que os clientes pensavam das suas lojas. Sabiam que os clientes hesitariam em apresentar queixas aos empregados da loja, mas seriam rápidos a colocá-las no Twitter. Ajudei-os a ingerir os dados do Twitter num lago de dados e a avaliar o sentimento dos comentários dos clientes, categorizando-os como positivos, neutros ou negativos. Quando leram os comentários ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.