你好! Shipping to Taiwan with premium packaging for just NT$300 

Ship to
Taiwan
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada Data Architecture: A Primer for the Data Scientist
Type
Physical Book
Publisher
Author
Year
2019
Language
English
Pages
431
Format
Paperback
ISBN13
9780128169162
Edition No.
2
Categories

Data Architecture: A Primer for the Data Scientist

W. H. Inmon; Daniel Linstedt; Mary Levins (Author) · Academic Press · Paperback

Data Architecture: A Primer for the Data Scientist - W. H. Inmon; Daniel Linstedt; Mary Levins

Cheaper New Book Imported to Taiwan
Delivery: 14 Sep - 23 Sep Shipping: 10 to 12 business days.
NT$ 2,392
Faster New Book Imported to Taiwan
Delivery: 02 Sep - 09 Sep Shipping: 2 to 2 business days.
NT$ 2,734
NT$ 2,392

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "Data Architecture: A Primer for the Data Scientist "

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.New case studies include expanded coverage of textual management and analyticsNew chapters on visualization and big dataDiscussion of new visualizations of the end-state architecture

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Paperback.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews