Menu

Zaloguj się

Twoje konto

×
Dodano do koszyka:
Pozycja znajduje się w koszyku, zwiększono ilość tej pozycji:
Zakupiłeś już tę pozycję:
Książkę możesz pobrać z biblioteki w panelu użytkownika
Pozycja znajduje się w koszyku
Przejdź do koszyka

Zawartość koszyka

ODBIERZ TWÓJ BONUS :: »

Szukaj

Zamknij

    Dostawa od 0,00zł

    TOP tytuł w super cenie » 50% taniej

    Principles of Data Fabric. Become a data-driven organization by implementing Data Fabric solutions efficiently Sonia Mezzetta

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Principles of Data Fabric. Become a data-driven organization by implementing Data Fabric solutions efficiently Sonia Mezzetta - okladka książki

    Principles of Data Fabric. Become a data-driven organization by implementing Data Fabric solutions efficiently Sonia Mezzetta - okladka książki

    Principles of Data Fabric. Become a data-driven organization by implementing Data Fabric solutions efficiently Sonia Mezzetta - audiobook MP3

    Principles of Data Fabric. Become a data-driven organization by implementing Data Fabric solutions efficiently Sonia Mezzetta - audiobook CD

    Autor:
    Sonia Mezzetta
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    188
    Dostępne formaty:
         PDF
         ePub
    Data can be found everywhere, from cloud environments and relational and non-relational databases to data lakes, data warehouses, and data lakehouses. Data management practices can be standardized across the cloud, on-premises, and edge devices with Data Fabric, a powerful architecture that creates a unified view of data. This book will enable you to design a Data Fabric solution by addressing all the key aspects that need to be considered.
    The book begins by introducing you to Data Fabric architecture, why you need them, and how they relate to other strategic data management frameworks. You’ll then quickly progress to grasping the principles of DataOps, an operational model for Data Fabric architecture. The next set of chapters will show you how to combine Data Fabric with DataOps and Data Mesh and how they work together by making the most out of it. After that, you’ll discover how to design Data Integration, Data Governance, and Self-Service analytics architecture. The book ends with technical architecture to implement distributed data management and regulatory compliance, followed by industry best practices and principles.
    By the end of this data book, you will have a clear understanding of what Data Fabric is and what the architecture looks like, along with the level of effort that goes into designing a Data Fabric solution.

    Wybrane bestsellery

    Selling helion.pl

    O autorze książki

    Sonia Mezzetta is a senior certified IBM architect working as a Data Fabric Program Director. She has an eye for detail and enjoys problem solving data pain points. She started her data management career in IBM as a data architect specializing in enterprise architectures. She is an expert in Data Fabric, DataOps, Data Governance, and Data Analytics. With over 20 years of experience, she has designed and architected several Enterprise data solutions. She has authored numerous data management white papers and has a master’s and bachelor’s degree in Computer Science. Sonia is originally from New York City, and currently resides in the area of Westchester County, New York.

    Packt Publishing - inne książki

    Zamknij

    Przenieś na półkę

    Proszę czekać...
    ajax-loader

    Zamknij

    Wybierz metodę płatności

    Ebook
    98,10 zł
    Dodaj do koszyka

    Wydawnictwo Naukowe Helion »

    Grafika Wydawnictwo Naukowe Helion. Dołącz do nas!
    Zamknij Pobierz aplikację mobilną Ebookpoint
    Zabrania się wykorzystania treści strony do celów eksploracji tekstu i danych (TDM), w tym eksploracji w celu szkolenia technologii AI i innych systemów uczenia maszynowego. It is forbidden to use the content of the site for text and data mining (TDM), including mining for training AI technologies and other machine learning systems.