Access methods for Big Data: current status and future directions
Heterogeneity, size, timeliness, difficulty & confidentiality problems with Big Data hinder advancement at all phases of the channel that can create value from data. Data analysis, organization, retrieval & modeling are initial challenges for Big Data. Data investigation is a clear traffic j...
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| Format: | Article |
| Language: | English |
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European Alliance for Innovation (EAI)
2017-12-01
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| Series: | EAI Endorsed Transactions on Scalable Information Systems |
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| Online Access: | http://eudl.eu/doi/10.4108/eai.28-12-2017.153520 |
| _version_ | 1818483798957883392 |
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| author | A. N. M. Bazlur Rashid |
| author_facet | A. N. M. Bazlur Rashid |
| author_sort | A. N. M. Bazlur Rashid |
| collection | DOAJ |
| description | Heterogeneity, size, timeliness, difficulty & confidentiality problems with Big Data hinder advancement at all phases of the channel that can create value from data. Data analysis, organization, retrieval & modeling are initial challenges for Big Data. Data investigation is a clear traffic jam in many applications, both due to lack of scalability of the core algorithms and due to the difficulty of the data that needs to be analyzed. Despite this, the appearance of the results and its understanding by non-technical experts is vital to extracting actionable knowledge. To defeat these, there is a need for novel architectures, techniques, algorithms & analytics to deal with it as well as to retrieve the value and unseen knowledge. Further, we need to build up efficient and optimized access methods for countless reasons such as velocity of Big Data. In this article, we present a brief overview of the current status of access methods for Big data and discuss a few promising research directions. |
| first_indexed | 2024-12-10T15:46:54Z |
| format | Article |
| id | doaj.art-721a18bc35a6414893b97aefc030a87e |
| institution | Directory Open Access Journal |
| issn | 2032-9407 |
| language | English |
| last_indexed | 2024-12-10T15:46:54Z |
| publishDate | 2017-12-01 |
| publisher | European Alliance for Innovation (EAI) |
| record_format | Article |
| series | EAI Endorsed Transactions on Scalable Information Systems |
| spelling | doaj.art-721a18bc35a6414893b97aefc030a87e2022-12-22T01:42:56ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Scalable Information Systems2032-94072017-12-0141511410.4108/eai.28-12-2017.153520Access methods for Big Data: current status and future directionsA. N. M. Bazlur Rashid0Assistant Professor (Computer), Department of Textile Machinery Design & Maintenance, Bangladesh University of Textiles, Dhaka – 1208, Bangladesh; anm.bazlur.rashid@gmail.comHeterogeneity, size, timeliness, difficulty & confidentiality problems with Big Data hinder advancement at all phases of the channel that can create value from data. Data analysis, organization, retrieval & modeling are initial challenges for Big Data. Data investigation is a clear traffic jam in many applications, both due to lack of scalability of the core algorithms and due to the difficulty of the data that needs to be analyzed. Despite this, the appearance of the results and its understanding by non-technical experts is vital to extracting actionable knowledge. To defeat these, there is a need for novel architectures, techniques, algorithms & analytics to deal with it as well as to retrieve the value and unseen knowledge. Further, we need to build up efficient and optimized access methods for countless reasons such as velocity of Big Data. In this article, we present a brief overview of the current status of access methods for Big data and discuss a few promising research directions.http://eudl.eu/doi/10.4108/eai.28-12-2017.153520access methodsanalyticsbig datadata miningdata science |
| spellingShingle | A. N. M. Bazlur Rashid Access methods for Big Data: current status and future directions EAI Endorsed Transactions on Scalable Information Systems access methods analytics big data data mining data science |
| title | Access methods for Big Data: current status and future directions |
| title_full | Access methods for Big Data: current status and future directions |
| title_fullStr | Access methods for Big Data: current status and future directions |
| title_full_unstemmed | Access methods for Big Data: current status and future directions |
| title_short | Access methods for Big Data: current status and future directions |
| title_sort | access methods for big data current status and future directions |
| topic | access methods analytics big data data mining data science |
| url | http://eudl.eu/doi/10.4108/eai.28-12-2017.153520 |
| work_keys_str_mv | AT anmbazlurrashid accessmethodsforbigdatacurrentstatusandfuturedirections |