My Account Log in

1 option

Foundations for architecting data solutions : managing successful data projects / Ted Malaska and Jonathan Seidman.

O'Reilly Online Learning: Academic/Public Library Edition Available online

View online
Format:
Book
Author/Creator:
Malaska, Ted, author.
Seidman, Jonathan, author.
Language:
English
Subjects (All):
Big data--Management.
Big data.
Database management.
Physical Description:
1 online resource (189 pages)
Edition:
First edition.
Place of Publication:
Beijing : O'Reilly, [2018]
System Details:
text file
Summary:
While many companies ponder implementation details such as distributed processing engines and algorithms for data analysis, this practical book takes a much wider view of big data development, starting with initial planning and moving diligently toward execution. Authors Ted Malaska and Jonathan Seidman guide you through the major components necessary to start, architect, and develop successful big data projects. Everyone from CIOs and COOs to lead architects and developers will explore a variety of big data architectures and applications, from massive data pipelines to web-scale applications. Each chapter addresses a piece of the software development life cycle and identifies patterns to maximize long-term success throughout the life of your project. Start the planning process by considering the key data project types Use guidelines to evaluate and select data management solutions Reduce risk related to technology, your team, and vague requirements Explore system interface design using APIs, REST, and pub/sub systems Choose the right distributed storage system for your big data system Plan and implement metadata collections for your data architecture Use data pipelines to ensure data integrity from source to final storage Evaluate the attributes of various engines for processing the data you collect
Contents:
Key data project types and considerations
Evaluating and selecting data management solutions
Managing risk in data projects
Interface design
Distributed storage systems
The meta of enterprise data
Ensuring data integrity
Data processing.
Notes:
Description based on print version record.
Includes index.
ISBN:
9781492038696
1492038695
9781492038733
1492038733
9781492038719
1492038717
OCLC:
1089811461

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Library Catalog Using Articles+ Library Account