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LEADER 00000uam a2200433 a 4500 
003    CaSebORM 
005    20210602143116.1 
006    m     o  d         
007    cr cn          
008    300421s2021    xx      o           eng   
020    |z9781098102753 
020    |z9781098102753 
024 8  9781098102760 
035    (CaSebORM)9781098102760 
041 0  eng 
100 1  Waddington, William,|eauthor. 
245 10 Architecting Data-Intensive SaaS Applications|h[O'Reilly 
       electronic resource] /|cWaddington, William. 
250    1st edition 
264  1 |bO'Reilly Media, Inc.,|c2021. 
300    1 online resource (67 pages) 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    text file 
365    |b74.99 
520    Through explosive growth in the past decade, data now 
       drives significant portions of our lives, from 
       crowdsourced restaurant recommendations to AI systems 
       identifying effective medical treatments. Software 
       developers have unprecedented opportunity to build data 
       applications that generate value from massive datasets 
       across use cases such as customer 360, application health 
       and security analytics, the IoT, machine learning, and 
       embedded analytics. With this report, product managers, 
       architects, and engineering teams will learn how to make 
       key technical decisions when building data-intensive 
       applications, including how to implement extensible data 
       pipelines and share data securely. The report includes 
       design considerations for making these decisions and uses 
       the Snowflake Data Cloud to illustrate best practices. 
       This report explores: Why data applications matter: Get an
       introduction to data applications and some of the most 
       common use cases Evaluating platforms for building data 
       apps: Evaluate modern data platforms to confidently 
       consider the merits of potential solutions Building 
       scalable data applications: Learn design patterns and best
       practices for storage, compute, and security Handling and 
       processing data: Explore techniques and real-world 
       examples for building data pipelines to support data 
       applications Designing for data sharing: Learn best 
       practices for sharing data in modern data applications 
533    Electronic reproduction.|bBoston, MA :|cSafari,|nAvailable
       via World Wide Web. 
538    Mode of access: World Wide Web. 
542    |fCopyright © 2021 O'Reilly Media, Inc. 
550    Made available through: Safari, an O'Reilly Media Company.
588 00 Online resource; Title from title page (viewed May 25, 
       2021) 
655  7 Electronic books.|2local 
700 1  McGinley, Kevin,|eauthor. 
700 1  Chu, Pui,|eauthor. 
700 1  Georgievski, Gjorgji,|eauthor. 
700 1  Kulkarni, Dinesh,|eauthor. 
710 2  Safari, an O'Reilly Media Company. 
856 40 |zConnect to this resource online|uhttps://
       ezproxy.naperville-lib.org/login?url=https://
       learning.oreilly.com/library/view/-/9781098102760/?ar