"If we didn't solve small data in the past, how can we solve Big Data today?"
Data is a critical aspect of the world we live in. With systems producing and consuming vast amounts of data, it is essential for businesses to digitally transform and be equipped to derive the most value out of data. Data analytics techniques can be used to augment strategic decision-making. While...
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| creator | Ravi, Akash |
| description | Data is a critical aspect of the world we live in. With systems producing and
consuming vast amounts of data, it is essential for businesses to digitally
transform and be equipped to derive the most value out of data. Data analytics
techniques can be used to augment strategic decision-making. While this overall
objective of data analytics remains fairly constant, the data itself can be
available in numerous forms and can be categorized under various contexts. In
this paper, we aim to research terms such as 'small' and 'big' data, understand
their attributes, and look at ways in which they can add value. Specifically,
the paper probes into the question "If we didn't solve small data in the past,
how can we solve Big Data today?". Based on the research, it can be inferred
that, regardless of how small data might have been used, organizations can
still leverage big data with the right technology and business vision. |
| doi_str_mv | 10.48550/arxiv.2111.04442 |
| format | Article |
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consuming vast amounts of data, it is essential for businesses to digitally
transform and be equipped to derive the most value out of data. Data analytics
techniques can be used to augment strategic decision-making. While this overall
objective of data analytics remains fairly constant, the data itself can be
available in numerous forms and can be categorized under various contexts. In
this paper, we aim to research terms such as 'small' and 'big' data, understand
their attributes, and look at ways in which they can add value. Specifically,
the paper probes into the question "If we didn't solve small data in the past,
how can we solve Big Data today?". Based on the research, it can be inferred
that, regardless of how small data might have been used, organizations can
still leverage big data with the right technology and business vision.</description><identifier>DOI: 10.48550/arxiv.2111.04442</identifier><language>eng</language><subject>Computer Science - Computers and Society</subject><creationdate>2021-11</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2111.04442$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2111.04442$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Ravi, Akash</creatorcontrib><title>"If we didn't solve small data in the past, how can we solve Big Data today?"</title><description>Data is a critical aspect of the world we live in. With systems producing and
consuming vast amounts of data, it is essential for businesses to digitally
transform and be equipped to derive the most value out of data. Data analytics
techniques can be used to augment strategic decision-making. While this overall
objective of data analytics remains fairly constant, the data itself can be
available in numerous forms and can be categorized under various contexts. In
this paper, we aim to research terms such as 'small' and 'big' data, understand
their attributes, and look at ways in which they can add value. Specifically,
the paper probes into the question "If we didn't solve small data in the past,
how can we solve Big Data today?". Based on the research, it can be inferred
that, regardless of how small data might have been used, organizations can
still leverage big data with the right technology and business vision.</description><subject>Computer Science - Computers and Society</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotjztvwjAUhb0wVNAf0KlXLF1I6ms7xJ5QS19IVF3Yo1s_iqWQoMSC8u9LoNM5R_p0pI-xO-S50kXBH6n7jYdcIGLOlVLihn1OVwGOHlx0zUOCvq0PHvod1TU4SgSxgbT1sKc-zWDbHsFSM_BX8Dn-wMuApdbRaTGdsFGguve3_zlmm7fXzfIjW3-9r5ZP64zmpcjmBeeODLfB8dIaHRC91M7xgAql9oTnqpU9TyMVoSBlvC2FxG9OojRyzO6vtxefat_FHXWnavCqLl7yD4GhRac</recordid><startdate>20211108</startdate><enddate>20211108</enddate><creator>Ravi, Akash</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20211108</creationdate><title>"If we didn't solve small data in the past, how can we solve Big Data today?"</title><author>Ravi, Akash</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a672-6500da90cfd07c98f11e38dd0f14138ea1d0f84cf14934a12a49ec7231b0a2793</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Computer Science - Computers and Society</topic><toplevel>online_resources</toplevel><creatorcontrib>Ravi, Akash</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ravi, Akash</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>"If we didn't solve small data in the past, how can we solve Big Data today?"</atitle><date>2021-11-08</date><risdate>2021</risdate><abstract>Data is a critical aspect of the world we live in. With systems producing and
consuming vast amounts of data, it is essential for businesses to digitally
transform and be equipped to derive the most value out of data. Data analytics
techniques can be used to augment strategic decision-making. While this overall
objective of data analytics remains fairly constant, the data itself can be
available in numerous forms and can be categorized under various contexts. In
this paper, we aim to research terms such as 'small' and 'big' data, understand
their attributes, and look at ways in which they can add value. Specifically,
the paper probes into the question "If we didn't solve small data in the past,
how can we solve Big Data today?". Based on the research, it can be inferred
that, regardless of how small data might have been used, organizations can
still leverage big data with the right technology and business vision.</abstract><doi>10.48550/arxiv.2111.04442</doi><oa>free_for_read</oa></addata></record> |
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| identifier | DOI: 10.48550/arxiv.2111.04442 |
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| subjects | Computer Science - Computers and Society |
| title | "If we didn't solve small data in the past, how can we solve Big Data today?" |
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