|
|
|
|
LEADER |
00000cam a2200000 i 4500 |
001 |
OR_on1078253662 |
003 |
OCoLC |
005 |
20231017213018.0 |
006 |
m o d |
007 |
cr unu|||||||| |
008 |
181206s2015 caua ob 000 0 eng d |
040 |
|
|
|a UMI
|b eng
|e rda
|e pn
|c UMI
|d TOH
|d OCLCF
|d STF
|d MERER
|d OCLCQ
|d CEF
|d C6I
|d OCLCQ
|d OCLCO
|d KSU
|d OCLCQ
|
029 |
1 |
|
|a AU@
|b 000065065814
|
035 |
|
|
|a (OCoLC)1078253662
|
037 |
|
|
|a CL0501000012
|b Safari Books Online
|
050 |
|
4 |
|a TS171
|
049 |
|
|
|a UAMI
|
100 |
1 |
|
|a Pavliscak, Pamela,
|e author.
|
245 |
1 |
0 |
|a Data-informed product design /
|c Pamela Pavliscak.
|
250 |
|
|
|a First edition.
|
264 |
|
1 |
|a Sebastopol, CA :
|b O'Reilly Media,
|c [2015]
|
264 |
|
4 |
|c ©2015
|
300 |
|
|
|a 1 online resource (1 volume) :
|b illustrations
|
336 |
|
|
|a text
|b txt
|2 rdacontent
|
337 |
|
|
|a computer
|b c
|2 rdamedia
|
338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
588 |
0 |
|
|a Online resource; title from title page (Safari, viewed December 4, 2018).
|
504 |
|
|
|a Includes bibliographical references.
|
520 |
|
|
|a The need to understand people lies at the core of any product design, and currently there are two standard ways to measure that understanding: big datasets and small research studies-aka "thick data." Most organizations favor big over thick, but in doing so they miss the larger picture. In this report, author Pamela Pavliscak outlines a way to use data of all kinds to understand the relationship between people and technology. Big data shows traces of interactions that people leave behind, but it doesn't reveal the whole story. By adding user stories, you can go beyond the "what" to discover why people behave as they do. Up until now, there hasn't been much information on how to combine quantitative big data with qualitative thick data. That's where this report can help. You'll learn: What to consider when using data to understand people Key differences between big data and small research studies Why organizations should combine big and thick data to understand human behavior, emotion, and language Which data sources or research methods work best in combination How to categorize and combine data effectively in metrics Methods for infusing design documents with data How to work across teams to understand customers This report is ideal for product designers and developers, data scientists, design researchers, and business strategists
|
590 |
|
|
|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
|
650 |
|
0 |
|a Product design.
|
650 |
|
0 |
|a Online social networks
|x Economic aspects.
|
650 |
|
0 |
|a Internet marketing.
|
650 |
|
6 |
|a Conception de produit.
|
650 |
|
6 |
|a Réseaux sociaux (Internet)
|x Aspect économique.
|
650 |
|
6 |
|a Marketing sur Internet.
|
650 |
|
7 |
|a Internet marketing.
|2 fast
|0 (OCoLC)fst00977272
|
650 |
|
7 |
|a Product design.
|2 fast
|0 (OCoLC)fst01763003
|
856 |
4 |
0 |
|u https://learning.oreilly.com/library/view/~/9781492048688/?ar
|z Texto completo (Requiere registro previo con correo institucional)
|
994 |
|
|
|a 92
|b IZTAP
|