Этот веб-сайт требует, чтобы для Вашего браузера был включен JavaScript.
Пожалуйста, включите JavaScript и перезагрузите страницу.
Для веб-сайта требуется, чтобы Ваш браузер разрешил использование файлов cookie для входа в систему.
Пожалуйста, активируйте cookies и перезагрузите страницу.
Carte romana
Carte rusa
Carte engleza
Vezi toate cartile
Top branduri cosmetica
Cosmetica Coreeana
Machiaj
Ingrijire ten
Ingrijire par
Ingrijire corp
Produse de baie
Igiena orala
Igiena intima
Igiena sexuala
Cosmetice barbati
Seturi cadou
Naturale si organice
Vezi toate cosmeticele
Top branduri dermatocosmetica
Protectie solara
Seturi cadou si pachete promo
Parfumuri pentru femei
Top branduri femei
Premium brands femei
Parfumuri unisex
Vezi toate parfumurile
Parfumuri pentru barbati
Top branduri barbati
Premium brands barbati
Jucarii si jocuri
Hrana si articole copii
Scutece si servetele
Rechizite si papetarie
Vezi toate produsele
Nutritie & Suplimente
Branduri
Certificate Cadou
Felicitari
Plicuri
Cutii si Accesorii
W. H. InmonData Architecture: A Primer for the Data Scientist: A Primer for the Data Scientist, Paperback
в Пункте приема от 99,9 лей
Даже распечатанный
Перед оплатой
Over the past 5 years, the concept of big data has matured, data science has grown exponentially, and data architecture has become a standard part of organizational decision-making. Throughout all this change, the basic principles that shape the architecture of data have remained the same. There remains a need for people to take a look at the "bigger picture" and to understand where their data fit into the grand scheme of things.
Data Architecture: A Primer for the Data Scientist, Second Edition addresses the larger architectural picture of how big data fits within the existing information infrastructure or data warehousing systems. This is an essential topic not only for data scientists, analysts, and managers but also for researchers and engineers who increasingly need to deal with large and complex sets of data. Until data are gathered and can be placed into an existing framework or architecture, they cannot be used to their full potential. Drawing upon years of practical experience and using numerous examples and case studies from across various industries, the authors seek to explain this larger picture into which big data fits, giving data scientists the necessary context for how pieces of the puzzle should fit together.
Мы хотели бы узнать Ваше мнение! Оценить и пересмотреть этот пункт
Нет ни одного отзыва от других пользователей.