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<front>
<journal-meta>
<journal-id journal-id-type="publisher">IJDSBDA</journal-id>
<journal-title>International Journal of Data Science and Big Data Analytics</journal-title>
<issn pub-type="epub">2710-2599</issn>
<publisher>
<publisher-name>SvedbergOpen</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="other">ijdsbda-1-3-003</article-id>
<doi-group>
<article-doi><ext-link ext-link-type="uri" xmlns:xlink="https://doi.org/" xlink:href="10.51483/IJDSBDA.1.3.2021.15-21">10.51483/IJDSBDA.1.3.2021.15-21</ext-link></article-doi>
</doi-group>
<article-categories>
<subj-group>
<subject>Research Paper</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Trends in Data Warehousing Technology</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Abimbola</surname><given-names>Bola</given-names></name>
<xref ref-type="aff" rid="aff001"><sup>1</sup></xref>
<xref ref-type="corresp" rid="cor001"><sup>&#x002A;</sup></xref>
</contrib>
</contrib-group>
<aff id="aff001"><sup>1</sup><instname>Universidad de Oviedo, Escuela Universitaria Jovellanos</instname>, <instaddress>Francisco Tomas y Valiente 33201 Gijon, Oviedo, 33006</instaddress>, <instcountry>Spain</instcountry>., E-mail: <email>UO285018@uniovi.es</email></aff>
<author-notes>
<corresp id="cor001"><sup>&#x002A;</sup>Corresponding author: Bola Abimbola, <instname>Universidad de Oviedo, Escuela Universitaria Jovellanos</instname>, <instaddress>Francisco Tom&#x00E1;s y Valiente, 33201 Gijon, Oviedo, 33006</instaddress>, <instcountry>Spain</instcountry>. E-mail: <email>UO285018@uniovi.es</email></corresp>
</author-notes>
<pub-date pub-type="ppub">
<month>11</month>
<year>2021</year>
</pub-date>
<volume>1</volume>
<issue>3</issue>
<fpage>15</fpage>
<lpage>21</lpage>
<abstract>
<title>Abstract</title>
<p>The research looks at the concepts associated with data warehousing. These include: cloud computing and big data analytics. By analyzing the growth of these technologies, it is possible to tell the trend in which data will take in the coming future. A lot of data is in use at the moment in very large packets and volumes. The technologies that are associated with data use are associated with data use are immense and greatly spread across all computing gadgets in use. Cell phones, microcomputers, and other computing gadgets all take advantage of data warehousing technology. The research presents a case for the proliferated use of big data technologies across the world. Data use, and data users are separated using the concept of &#x2018;abstraction.&#x2019; As users continue to use big data analytics and warehousing more often, they are less aware of the dangers and concerns in the use and reliance of virtual computing facilities. The study seeks to establish the influence of current technologies on data warehousing and how they lead to the growth of data storage units across the globe. The survey on data warehousing trends is focused on software technologies that highly rely on the data warehousing facilities. Social media is acknowledged as one of the leading factors behind the growth of data warehousing facilities. This research seeks to establish the use of data in social media and other applications. The concept of data analytics is stressed as a key issue in data warehousing. Being that the data in warehouses is highly sophisticated and voluminous; the need for specialized software to undertake sorting and searching purposes is reviewed. The study seeks to establish that the use of big data is an important concept as well. This concept is evaluated and well explained. The concerns with data warehousing are also evaluated in an effort to realize more need to secure data. The research concludes with an appeal for user awareness on data warehouse capabilities. Users are expected to be more aware of the purpose and capability of data and in essence, use these facilities from a professional point of view; not as novices.</p>
</abstract>
<kwd-group>
<title>Keywords</title>
<kwd>Data warehouse</kwd>
<kwd>Big Data</kwd>
<kwd>Virtual storage</kwd>
<kwd>Cloud storage</kwd>
</kwd-group>
<counts>
<ref-count count="19"/>
<page-count count="7"/>
</counts>
</article-meta>
</front>
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<ref-list>
<title>References</title>
<ref id="bib001"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Abello&#x2019;</surname><given-names>A.</given-names></name><name><surname>Darmont</surname><given-names>J.</given-names></name><name><surname>Etcheverry</surname><given-names>L.</given-names></name><name><surname>Golfarelli</surname><given-names>M.</given-names></name><name><surname>Mazo&#x2019;nLo&#x2019;pez</surname><given-names>J. N.</given-names></name><name><surname>Naumann</surname><given-names>F.</given-names></name><name><surname>Vossen</surname><given-names>G.</given-names></name></person-group> (<year>2013</year>). <article-title>Fusion Cubes: Towards Self-Service Business Intelligence</article-title>. <source>International Journal of Data Warehousing and Mining</source>, <volume>9</volume>(<issue>2</issue>), <fpage>66</fpage>&#x2013;<lpage>88</lpage>.</citation></ref>
<ref id="bib002"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Aji</surname><given-names>A.</given-names></name><name><surname>Wang</surname><given-names>F.</given-names></name><name><surname>Vo</surname><given-names>H.</given-names></name><name><surname>Lee</surname><given-names>R.</given-names></name><name><surname>Liu</surname><given-names>Q.</given-names></name><name><surname>Zhang</surname><given-names>X.</given-names></name><name><surname>Saltz</surname><given-names>J.</given-names></name></person-group> (<year>2013</year>). <article-title>Hadoop GIS: A High Performance Spatial Data Warehousing System Over Map-Reduce</article-title>. <source>Proceedings of the VLDB Endowment</source>, <volume>6</volume>(<issue>11</issue>), <fpage>1009</fpage>&#x2013;<lpage>1020</lpage>.</citation></ref>
<ref id="bib003"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Bennett</surname><given-names>M.</given-names></name></person-group> (<year>2016</year>). <article-title>An Industry Ontology for Risk Data Aggregation Reporting</article-title>. <source>Journal of Securities Operations Custody</source>, <volume>8</volume>(<issue>2</issue>), <fpage>132</fpage>&#x2013;<lpage>145</lpage>.</citation></ref>
<ref id="bib004"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Chen</surname><given-names>H.</given-names></name><name><surname>Chiang</surname><given-names>R.H.</given-names></name><name><surname>Storey</surname><given-names>V.C.</given-names></name></person-group> (<year>2012</year>). <article-title>Business Intelligence and Analytics: From Big Data to Big Impact</article-title>. <source>MIS Quarterly</source>, <volume>36</volume>(<issue>4</issue>), <fpage>1165</fpage>&#x2013;<lpage>1188</lpage>.</citation></ref>
<ref id="bib005"><citation citation-type="book"><person-group person-group-type="author"><name><surname>Erickson</surname><given-names>P.</given-names></name></person-group> (<year>2013</year>). <source>Data Warehouse: 82 Most Asked Questions: What You Need to Know</source>. <publisher-name>Emereo Publishing</publisher-name>. <publisher-loc>Brisbane, Australia</publisher-loc>.</citation></ref>
<ref id="bib006"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Gersil</surname><given-names>M.</given-names></name></person-group> (<year>2016</year>). <article-title>Data Mining Practice in the Scope of CRM: Churn Management in the Telecommunication Sector</article-title>. <source>International Journal of Business Management Economic Research</source>, <volume>7</volume>(<issue>2</issue>), <fpage>560</fpage>&#x2013;<lpage>567</lpage>.</citation></ref>
<ref id="bib007"><citation citation-type="book"><person-group person-group-type="author"><name><surname>Gonzalez</surname><given-names>H.</given-names></name><name><surname>Halevy</surname><given-names>A.</given-names></name><name><surname>Jensen</surname><given-names>C. S.</given-names></name><name><surname>Langen</surname><given-names>A.</given-names></name><name><surname>Madhavan</surname><given-names>J.</given-names></name><name><surname>Shapley</surname><given-names>R.</given-names></name><name><surname>Shen</surname><given-names>W.</given-names></name></person-group> (<year>2010</year>). <chapter-title>Google Fusion Tables: Data Management, Integration and Collaboration in the Cloud</chapter-title>. In <source>Proceedings of the 1<sup>st</sup> ACM Symposium on Cloud Computing</source> (pp. <fpage>175</fpage>&#x2013;<lpage>180</lpage>). <publisher-name>ACM</publisher-name>.</citation></ref>
<ref id="bib008"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Halter</surname><given-names>O.</given-names></name><name><surname>Kromer</surname><given-names>M.</given-names></name><name><surname>Kutemperor</surname><given-names>N.</given-names></name><name><surname>Soares</surname><given-names>D.</given-names></name></person-group> (<year>2016</year>). <article-title>Dipping a Toe into Data Lakes</article-title>. <source>Business Intelligence Journal</source>, <volume>21</volume>(<issue>2</issue>), <fpage>40</fpage>&#x2013;<lpage>46</lpage>.</citation></ref>
<ref id="bib009"><citation citation-type="book"><person-group person-group-type="author"><name><surname>Haq</surname><given-names>Q.U.</given-names></name></person-group> (<year>2016</year>). <source>Data Mapping for Data Warehouse Design</source>. <publisher-loc>Amsterdam</publisher-loc>: <edition>1st</edition> Edition - <month>December</month> <day>8</day>, 2015. Author: <publisher-name>Qamar Shahbaz, eBook</publisher-name> ISBN: <isbn>9780128053355</isbn>. Paperback ISBN: 9780128051856.</citation></ref>
<ref id="bib010"><citation citation-type="book"><person-group person-group-type="author"><name><surname>Inmon</surname><given-names>W. H.</given-names></name><name><surname>Strauss</surname><given-names>D.</given-names></name><name><surname>Neushloss</surname><given-names>G</given-names></name></person-group> (<year>2010</year>). <source>DW 2.0: The Architecture for the Next Generation of Data Warehousing</source>. <edition>1<sup>st</sup></edition> Edition, <publisher-name>Morgan Kaufmann Publishers</publisher-name>. <publisher-loc>USA</publisher-loc>.</citation></ref>
<ref id="bib011"><citation citation-type="book"><person-group person-group-type="author"><name><surname>Krishnan</surname><given-names>K.</given-names></name></person-group> (<year>2013</year>). <source>Data Warehousing in the Age of Big Data</source>. <edition>1st</edition> Edition, <publisher-name>Morgan Kaufmann Publishers</publisher-name>. <publisher-loc>USA</publisher-loc>.</citation></ref>
<ref id="bib012"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Kutemperor</surname><given-names>N.T.</given-names></name></person-group> (<year>2015</year>). <article-title>Price/Performance Considerations in Building Data Warehouses for Big Data</article-title>. <source>Business Intelligence Journal</source>, <volume>20</volume>(<issue>2</issue>), <fpage>8</fpage>&#x2013;<lpage>13</lpage>.</citation></ref>
<ref id="bib013"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>March</surname><given-names>S.T.</given-names></name><name><surname>Hevner</surname><given-names>A.R.</given-names></name></person-group> (<year>2007</year>). <article-title>Integrated Decision Support Systems: A Data Warehousing Perspective</article-title>. <source>Decision Support Systems</source>, <volume>43</volume>(<issue>3</issue>), <fpage>1031</fpage>&#x2013;<lpage>1043</lpage>.</citation></ref>
<ref id="bib014"><citation citation-type="book"><person-group person-group-type="editor"><name><surname>Miller</surname><given-names>H.J.</given-names></name><name><surname>Han</surname><given-names>J.</given-names></name></person-group> (Eds.).(<year>2009</year>). <source>Geographic Data Mining and Knowledge Discovery</source>. <publisher-name>CRC Press</publisher-name>.</citation></ref>
<ref id="bib015"><citation citation-type="other"><person-group person-group-type="author"><name><surname>Revels</surname><given-names>M.</given-names></name><name><surname>Nussbaumer</surname><given-names>H.</given-names></name></person-group> (<year>2013</year>). <article-title>Data Mining and Data Warehousing in the Airline Industry</article-title>. <source>Academy of Business Research Journal</source>, <fpage>369</fpage>&#x2013;<lpage>82</lpage>.</citation></ref>
<ref id="bib016"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sremack</surname><given-names>J.</given-names></name></person-group> (<year>2015</year>). <article-title>Responding to a Legal Data Request: The Role of the Data Warehouse Team</article-title>. <source>Business Intelligence Journal</source>, <volume>20</volume>(<issue>1</issue>), <fpage>39</fpage>&#x2013;<lpage>43</lpage>.</citation></ref>
<ref id="bib017"><citation citation-type="other"><person-group person-group-type="author"><name><surname>Takecian</surname><given-names>P. L.</given-names></name><name><surname>Oikawa</surname><given-names>M.K.</given-names></name><name><surname>Braghetto</surname><given-names>K.R.</given-names></name><name><surname>Rocha</surname><given-names>P.</given-names></name><name><surname>Lucena</surname><given-names>F.</given-names></name><name><surname>Kavounis</surname><given-names>K.</given-names></name><name><surname>Ferreira</surname><given-names>J.E.</given-names></name></person-group> (<year>2013</year>). <article-title>Methodological Guidelines for Reducing the Complexity of Data Warehouse Development for Transactional Blood Bank Systems</article-title>. <source>Decision Support Systems</source>, <fpage>55728</fpage>&#x2013;<lpage>739</lpage>. doi:<pub-id pub-id-type="doi">10.1016/j.dss.2013.02.008</pub-id></citation></ref>
<ref id="bib018"><citation citation-type="book"><person-group person-group-type="author"><name><surname>Thusoo</surname><given-names>A.</given-names></name><name><surname>Shao</surname><given-names>Z.</given-names></name><name><surname>Anthony</surname><given-names>S.</given-names></name><name><surname>Borthakur</surname><given-names>D.</given-names></name><name><surname>Jain</surname><given-names>N.</given-names></name><name><surname>SenSarma</surname><given-names>J.</given-names></name><name><surname>Liu</surname><given-names>H.</given-names></name></person-group> (<year>2010</year>). <chapter-title>Data Warehousing and Analytics Infrastructure at Facebook</chapter-title>. In <source>Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data</source> (pp. <fpage>1013</fpage>&#x2013;<lpage>1020</lpage>). <publisher-name>ACM</publisher-name>.</citation></ref>
<ref id="bib019"><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Watson</surname><given-names>A.</given-names></name><name><surname>Watson</surname><given-names>B.</given-names></name><name><surname>Vallmuur</surname><given-names>K.</given-names></name></person-group> (<year>2015</year>). <article-title>Estimating Under Reporting of Road Crash Injuries to Police Using Multiple Linked Data Collections</article-title>. <source>Accident Analysis and Prevention</source>, <volume>8</volume>(<issue>3</issue>), <fpage>18</fpage>&#x2013;<lpage>25</lpage>. doi:<pub-id pub-id-type="doi">10.1016/j.aap.2015.06.011</pub-id></citation></ref>
</ref-list>
</back>
</article>