Publicação
Enhancing big data warehousing for efficient, integrated and advanced analytics visionary paper
| Resumo: | The existing capacity to collect, store, process and analyze huge amounts of data that is rapidly generated, i.e., Big Data, is characterized by fast technological developments and by a limited set of conceptual advances that guide researchers and practitioners in the implementation of Big Data systems. New data stores or processing tools frequently appear, proposing new (and usually more efficient) ways to store and query data (like SQL-on-Hadoop). Although very relevant, the lack of common methodological guidelines or practices has motivated the implementation of Big Data systems based on use-case driven approaches. This is also the case for one of the most valuable organizational data assets, the Data Warehouse, which needs to be rethought in the way it is designed, modeled, implemented, managed and monitored. This paper addresses some of the research challenges in Big Data Warehousing systems, proposing a vision that looks into: (i) the integration of new business processes and data sources; (ii) the proper way to achieve this integration; (iii) the management of these complex data systems and the enhancement of their performance; (iv) the automation of some of their analytical capabilities with Complex Event Processing and Machine Learning; and, (v) the flexible and highly customizable visualization of their data, providing an advanced decision-making support environment. |
|---|---|
| Autores principais: | Santos, Maribel Yasmina |
| Outros Autores: | Costa, Carlos A. P.; Galvão, João Rui Magalhães Velho da Cunha; Andrade, Carina; Pastor, Oscar; Cristina Marcen, Ana |
| Assunto: | Big data warehouse Data governance Data profiling Event processing Performance |
| Ano: | 2019 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| _version_ | 1866877424536387584 |
|---|---|
| author | Santos, Maribel Yasmina |
| author2 | Costa, Carlos A. P. Galvão, João Rui Magalhães Velho da Cunha Andrade, Carina Pastor, Oscar Cristina Marcen, Ana |
| author2_role | author author author author author |
| author_facet | Santos, Maribel Yasmina Costa, Carlos A. P. Galvão, João Rui Magalhães Velho da Cunha Andrade, Carina Pastor, Oscar Cristina Marcen, Ana |
| author_role | author |
| contributor_name_str_mv | Universidade do Minho |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Santos, Maribel Yasmina\"},{\"Person.name\":\"Costa, Carlos A. P.\"},{\"Person.name\":\"Galvão, João Rui Magalhães Velho da Cunha\"},{\"Person.name\":\"Andrade, Carina\"},{\"Person.name\":\"Pastor, Oscar\"},{\"Person.name\":\"Cristina Marcen, Ana\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Universidade do Minho |
| datacite.creators.creator.creatorName.fl_str_mv | Santos, Maribel Yasmina Costa, Carlos A. P. Galvão, João Rui Magalhães Velho da Cunha Andrade, Carina Pastor, Oscar Cristina Marcen, Ana |
| datacite.date.Accepted.fl_str_mv | 2019-01-01T00:00:00Z |
| datacite.date.embargoed.fl_str_mv | 10000-01-01T00:00:00Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_16ec |
| datacite.subjects.subject.fl_str_mv | Big data warehouse Data governance Data profiling Event processing Performance |
| datacite.titles.title.fl_str_mv | Enhancing big data warehousing for efficient, integrated and advanced analytics visionary paper |
| dc.contributor.none.fl_str_mv | Universidade do Minho |
| dc.creator.none.fl_str_mv | Santos, Maribel Yasmina Costa, Carlos A. P. Galvão, João Rui Magalhães Velho da Cunha Andrade, Carina Pastor, Oscar Cristina Marcen, Ana |
| dc.date.Accepted.fl_str_mv | 2019-01-01T00:00:00Z |
| dc.date.embargoed.fl_str_mv | 10000-01-01T00:00:00Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://hdl.handle.net/1822/66801 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Springer Verlag |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_16ec |
| dc.subject.none.fl_str_mv | Big data warehouse Data governance Data profiling Event processing Performance |
| dc.title.fl_str_mv | Enhancing big data warehousing for efficient, integrated and advanced analytics visionary paper |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_5794 |
| description | The existing capacity to collect, store, process and analyze huge amounts of data that is rapidly generated, i.e., Big Data, is characterized by fast technological developments and by a limited set of conceptual advances that guide researchers and practitioners in the implementation of Big Data systems. New data stores or processing tools frequently appear, proposing new (and usually more efficient) ways to store and query data (like SQL-on-Hadoop). Although very relevant, the lack of common methodological guidelines or practices has motivated the implementation of Big Data systems based on use-case driven approaches. This is also the case for one of the most valuable organizational data assets, the Data Warehouse, which needs to be rethought in the way it is designed, modeled, implemented, managed and monitored. This paper addresses some of the research challenges in Big Data Warehousing systems, proposing a vision that looks into: (i) the integration of new business processes and data sources; (ii) the proper way to achieve this integration; (iii) the management of these complex data systems and the enhancement of their performance; (iv) the automation of some of their analytical capabilities with Complex Event Processing and Machine Learning; and, (v) the flexible and highly customizable visualization of their data, providing an advanced decision-making support environment. |
| dirty | 0 |
| eu_rights_str_mv | restrictedAccess |
| format | conferencePaper |
| fulltext.url.fl_str_mv | https://prod-dspace.uminho.pt/bitstreams/64940fa4-cfc1-499b-8a3a-12d0af6e2cbd/download |
| id | rum_6fa8d8ecbc3e67a2d439e09d96d10e30 |
| identifier.url.fl_str_mv | https://hdl.handle.net/1822/66801 |
| instacron_str | repositorium |
| institution | Universidade do Minho |
| instname_str | Universidade do Minho |
| language | eng |
| network_acronym_str | rum |
| network_name_str | RepositóriUM - Universidade do Minho |
| oai_identifier_str | oai:repositorium.uminho.pt:1822/66801 |
| organization_str_mv | urn:organizationAcronym:repositorium |
| person_str_mv | Santos, Maribel Yasmina Costa, Carlos A. P. Galvão, João Rui Magalhães Velho da Cunha Andrade, Carina Pastor, Oscar Cristina Marcen, Ana |
| publishDate | 2019 |
| publisher.none.fl_str_mv | Springer Verlag |
| reponame_str | RepositóriUM - Universidade do Minho |
| repository_id_str | urn:repositoryAcronym:rum |
| service_str_mv | urn:repositoryAcronym:rum |
| spelling | engSpringer VerlagporThe existing capacity to collect, store, process and analyze huge amounts of data that is rapidly generated, i.e., Big Data, is characterized by fast technological developments and by a limited set of conceptual advances that guide researchers and practitioners in the implementation of Big Data systems. New data stores or processing tools frequently appear, proposing new (and usually more efficient) ways to store and query data (like SQL-on-Hadoop). Although very relevant, the lack of common methodological guidelines or practices has motivated the implementation of Big Data systems based on use-case driven approaches. This is also the case for one of the most valuable organizational data assets, the Data Warehouse, which needs to be rethought in the way it is designed, modeled, implemented, managed and monitored. This paper addresses some of the research challenges in Big Data Warehousing systems, proposing a vision that looks into: (i) the integration of new business processes and data sources; (ii) the proper way to achieve this integration; (iii) the management of these complex data systems and the enhancement of their performance; (iv) the automation of some of their analytical capabilities with Complex Event Processing and Machine Learning; and, (v) the flexible and highly customizable visualization of their data, providing an advanced decision-making support environment.application/pdfporEnhancing big data warehousing for efficient, integrated and advanced analytics visionary paperSantos, Maribel YasminaCosta, Carlos A. P.Galvão, João Rui Magalhães Velho da CunhaAndrade, CarinaPastor, OscarCristina Marcen, AnaHostingInstitutionOrganizationalUniversidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.ptISBNIsPartOf9783030212964ISSNIsPartOf1865-1348DOIIsPartOf10.1007/978-3-030-21297-1_1920192020-09-04T15:13:26Z10000-01-01T00:00:00Z2019-01-01T00:00:00ZHandlehttps://hdl.handle.net/1822/66801http://purl.org/coar/access_right/c_16ecrestricted accessBig data warehouseData governanceData profilingEvent processingPerformance596154 bytesother research producthttp://purl.org/coar/resource_type/c_5794conference paperhttp://purl.org/coar/access_right/c_f1cfapplication/pdffulltexthttps://prod-dspace.uminho.pt/bitstreams/64940fa4-cfc1-499b-8a3a-12d0af6e2cbd/download |
| spellingShingle | Enhancing big data warehousing for efficient, integrated and advanced analytics visionary paper Santos, Maribel Yasmina Big data warehouse Data governance Data profiling Event processing Performance |
| status | SINGLETON |
| subject.fl_str_mv | Big data warehouse Data governance Data profiling Event processing Performance |
| title | Enhancing big data warehousing for efficient, integrated and advanced analytics visionary paper |
| title_full | Enhancing big data warehousing for efficient, integrated and advanced analytics visionary paper |
| title_fullStr | Enhancing big data warehousing for efficient, integrated and advanced analytics visionary paper |
| title_full_unstemmed | Enhancing big data warehousing for efficient, integrated and advanced analytics visionary paper |
| title_short | Enhancing big data warehousing for efficient, integrated and advanced analytics visionary paper |
| title_sort | Enhancing big data warehousing for efficient, integrated and advanced analytics visionary paper |
| topic | Big data warehouse Data governance Data profiling Event processing Performance |
| topic_facet | Big data warehouse Data governance Data profiling Event processing Performance |
| url | https://hdl.handle.net/1822/66801 |
| visible | 1 |