Logo do repositório
 
Publicação

Digital analytics: an approach for data quality control

2022-01-25Dissertação de mestrado Acesso aberto
Ver registo simples
dc.contributor.advisorAntónio, Nuno Miguel da Conceição
dc.contributor.authorMarques, Ana Rita Xavier
dc.date.accessioned2022-03-03T16:50:03Z
dc.date.available2022-03-03T16:50:03Z
dc.date.issued2022-01-25
dc.descriptionInternship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Sciencept_PT
dc.description.abstractWith the emergence of the Digital Era, a new way of analyzing customers' behavior also emerged. It's not only about analyzing data from traditional data warehouses but also about measuring users' digital footprint on websites, mobile applications, and other digital data sources. Nowadays, companies collect data on their digital channels to improve website design and user experience, optimize e-commerce, track, and measure the success of actions and programs, identify problems, and improve the digital channels' performance. But the question that arises is how valid, accurate, and complete the data is. Do digital analysts understand each data point they have at their disposal? In this internship report will be given a detailed view of the critical points of digital analytics data quality, the adjacent problems and a solution will be presented to support and help the digital analysts overcome some of the challenges in this area.pt_PT
dc.identifier.tid202962288pt_PT
dc.identifier.urihttp://hdl.handle.net/10362/133843
dc.language.isoengpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectDigital Analyticspt_PT
dc.subjectData Qualitypt_PT
dc.subjectData Catalogingpt_PT
dc.subjectWeb Crawlerpt_PT
dc.subjectTrackingpt_PT
dc.titleDigital analytics: an approach for data quality controlpt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameMestrado em Ciência de Dados e Métodos Analíticos Avançados, especialização em Ciência de Dadospt_PT

Ficheiros

Principais
A mostrar 1 - 1 de 1
Miniatura
Nome:
TCDMAA0124.pdf
Tamanho:
1.61 MB
Formato:
Adobe Portable Document Format
Ver/Abrir

Coleções

NIMS - Dissertações de Mestrado em Ciência de Dados e Métodos Analíticos Avançados (Data Science and Advanced Analytics)