How Big Data Affects UserExperienceReducing cognitive load in big data applications

We have entered the age of big data. Massive data sets are common in enterprises, government, and academia. Interpreting such scales of data is still hard for the human mind. This thesis investigates how proper design can decrease the cognitive load in data-heavy applications. It focuses on numeric...

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Bibliographic Details
Main Author: Kämpe, Gabriella
Format: Others
Language:English
Published: Umeå universitet, Institutionen för datavetenskap 2019
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-163995
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spelling ndltd-UPSALLA1-oai-DiVA.org-umu-1639952019-10-12T04:31:32ZHow Big Data Affects UserExperienceReducing cognitive load in big data applicationsengKämpe, GabriellaUmeå universitet, Institutionen för datavetenskap2019Engineering and TechnologyTeknik och teknologierWe have entered the age of big data. Massive data sets are common in enterprises, government, and academia. Interpreting such scales of data is still hard for the human mind. This thesis investigates how proper design can decrease the cognitive load in data-heavy applications. It focuses on numeric data describing economic growth in retail organizations. It aims to answer the questions: What is important to keep in mind when designing an interface that holds large amounts of data? and How to decrease the cognitive load in complex user interfaces without reducing functionality?. It aims to answer these questions by comparing two user interfaces in terms of efficiency, structure, ease of use and navigation. Each interface holds the same functionality and amount of data, but one is designed to increase user experience by reducing cognitive load. The design choices in the second application are based on the theory found in the literature study in the thesis. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-163995UMNAD ; 1201application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic Engineering and Technology
Teknik och teknologier
spellingShingle Engineering and Technology
Teknik och teknologier
Kämpe, Gabriella
How Big Data Affects UserExperienceReducing cognitive load in big data applications
description We have entered the age of big data. Massive data sets are common in enterprises, government, and academia. Interpreting such scales of data is still hard for the human mind. This thesis investigates how proper design can decrease the cognitive load in data-heavy applications. It focuses on numeric data describing economic growth in retail organizations. It aims to answer the questions: What is important to keep in mind when designing an interface that holds large amounts of data? and How to decrease the cognitive load in complex user interfaces without reducing functionality?. It aims to answer these questions by comparing two user interfaces in terms of efficiency, structure, ease of use and navigation. Each interface holds the same functionality and amount of data, but one is designed to increase user experience by reducing cognitive load. The design choices in the second application are based on the theory found in the literature study in the thesis.
author Kämpe, Gabriella
author_facet Kämpe, Gabriella
author_sort Kämpe, Gabriella
title How Big Data Affects UserExperienceReducing cognitive load in big data applications
title_short How Big Data Affects UserExperienceReducing cognitive load in big data applications
title_full How Big Data Affects UserExperienceReducing cognitive load in big data applications
title_fullStr How Big Data Affects UserExperienceReducing cognitive load in big data applications
title_full_unstemmed How Big Data Affects UserExperienceReducing cognitive load in big data applications
title_sort how big data affects userexperiencereducing cognitive load in big data applications
publisher Umeå universitet, Institutionen för datavetenskap
publishDate 2019
url http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-163995
work_keys_str_mv AT kampegabriella howbigdataaffectsuserexperiencereducingcognitiveloadinbigdataapplications
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