{"id":3777,"date":"2020-03-11T08:37:02","date_gmt":"2020-03-11T12:37:02","guid":{"rendered":"http:\/\/icaninfotech.com\/?p=3777"},"modified":"2024-07-29T10:08:31","modified_gmt":"2024-07-29T10:08:31","slug":"data-science-trends-in-2020","status":"publish","type":"post","link":"https:\/\/icaninfotech.com\/data-science-trends-in-2020\/","title":{"rendered":"Data Science Trends in 2020"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"3777\" class=\"elementor elementor-3777\">\n\t\t\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-507e388b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"507e388b\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"has_eae_slider elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-541c1f4a\" data-id=\"541c1f4a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\n\t\t<div class=\"elementor-element elementor-element-4c3fc6c2 elementor-widget elementor-widget-text-editor\" data-id=\"4c3fc6c2\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.23.0 - 25-07-2024 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p>Source: dataversity<\/p><p>The exponential growth of data, partly generated by sensor-driven devices, is making Data Science and machine learning (ML) market differentiators in global business-analytics solutions. With the rising demand in\u00a0<a href=\"http:\/\/www.dataversity.net\/what-is-data-science\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">Data Science<\/a>\u00a0and ML skills, 2020 may well be a witness to several new trends in the field.<\/p><p><a href=\"https:\/\/www.emc.com\/leadership\/digital-universe\/2014iview\/executive-summary.htm\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">According to IDC:<\/a><\/p><p>\u201c[I]f our digital universe or total data content were represented by tablets, then by 2020 they would stretch all the way to the moon over six times. That\u2019s equal to 44 zettabytes of data, or 44 trillion gigabytes.\u201d<\/p><p>They made that prediction back in 2014 and it has certainly become true.<\/p><p>Towards Data Science\u00a0<a href=\"https:\/\/towardsdatascience.com\/what-does-the-future-of-data-science-hold-for-you-7ae47861dc22?gi=730fdfb044da\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">reports:<\/a><\/p><ul><li>Currently, the daily data output is more than 2.5 quintillion bytes.<\/li><li>In the near future, \u201c1.7 Mb of data will be created every second for every person on the planet.\u201d<\/li><li>A wide variety of Data Science roles will drive these massive data loads.<\/li><li><h4><strong>Trend One: Growth of Data Science Roles in 2020<\/strong><\/h4><p>IBM predicted that the demand for data scientists will increase by 28 per cent by 2020. Another report <a href=\"https:\/\/www.bmmagazine.co.uk\/business\/data-science-will-grow-in-scope-by-2020\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">indicates<\/a>\u00a0that in 2020, Data Science roles will expand to include machine learning (ML) and big data technology skills \u2014 especially given the rapid adoption of cloud and IoT technologies across global businesses.<\/p><p>In 2020, enterprises will demand more from their\u00a0<a href=\"https:\/\/www.mastersindatascience.org\/schools\/data-science-degrees-online\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\"in-house data scientists (opens in a new tab)\">in-house data scientists<\/a>, and these special experts will be viewed as \u201cwizards of all business solutions.\u201d Another thing to note is that the annual demand for Data Science roles, which includes\u00a0<a href=\"https:\/\/www.dataversity.net\/data-scientist-vs-data-engineer\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">data engineers<\/a>, data analysts, data developers and others, will hit the 700,000 marks next year.<\/p><p>This\u00a0<a href=\"https:\/\/data-flair.training\/blogs\/data-science-job-trends\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">Data Flair post<\/a> explains the shades of differences among Data Science roles such as data engineers and data architects. If you have just entered the field of Data Science, you may want to explore the\u00a0<a href=\"https:\/\/medium.com\/towards-artificial-intelligence\/10-questions-to-consider-before-pursuing-a-career-in-data-science-9fc6a1c92ba3\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">10 questions to ask before making a career decision<\/a>.<\/p><p>IBM, Burning Glass Technologies, and Business-Higher Education Forum (BHEF) forged a \u201c<a href=\"https:\/\/www.forbes.com\/sites\/louiscolumbus\/2017\/05\/13\/ibm-predicts-demand-for-data-scientists-will-soar-28-by-2020\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">research partnership<\/a>\u201d to reduce the existing skill gaps in Data Science and business analytics with the help of actionable insights currently shared between the academia and the industry.\u00a0<a href=\"https:\/\/www.bhef.com\/publications\/quant-crunch-how-demand-data-science-skills-disrupting-job-market\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">These insights<\/a>\u00a0can be found in\u00a0<em>The Quant Crunch: How the Demand For Data Science Skills Is Disrupting the Job Market<\/em>.<\/p><p><em><a href=\"https:\/\/www.dataversity.net\/data-scientist-future-will\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">The Data Scientist of the Future: What Will They Be Doing?<\/a><\/em>\u00a0discusses the gradual evolution of the Data Science role into more of a collaborator and a facilitator role, rather than that of a technical expert.<\/p><h4><strong>Trend Two: Widespread Automation in Data Science<\/strong><\/h4><p>As an\u00a0<a href=\"https:\/\/www.analyticsinsight.net\/gartner-and-forresters-take-on-automation-predictions-for-2020\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">Analytics Insights article<\/a>\u00a0suggests, a Forrester report titled\u00a0<em>Predictions 2020: Automation<\/em> includes a warning that \u201cover a million knowledge-work jobs will be replaced by software robotics, RPA, virtual agents and chatbots and ML-based decision management.\u201d In another report, Forrester has warned that automation in untrained hands can lead to potential hazards. A phenomenon called \u201chyper-automation,\u201d or an uncomfortable blend of multiple ML applications and other technology platforms may render data-technology ecosystems unsustainable in about 80 per cent of enterprises.<\/p><h4><strong>Trend Three: Evolution of Big Data in AI-Ready Data Landscape<\/strong><\/h4><p>Big data analytics received a major push across global businesses in 2019 when data scientists partnered with data engineers and data analysts to mobilize the mainstream use of AI and ML algorithms across business analytics platforms. Automation of Data Science tasks was a big thing in 2019. In 2020, this automation frenzy in Data Science will continue, enabling data scientists \u201cto create their own, near production-ready data pipelines.\u201d As data sources become more varied and complicated and automation of Data Science prevails, businesses may experience more innovations in big data analytics.<\/p><p>2020 will also witness the major analytics vendors rolling out integrated platforms with more automated Data Management features and benefits.\u00a0<em><a href=\"https:\/\/www.dataversity.net\/data-science-trends-in-2019\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">Data Science Trends in 2019<\/a><\/em>\u00a0pointed out that though big data has \u201ctaken Data Science forward by leaps and bounds,\u201d AI and related data technologies have now confronted dig data with many logistic issues difficult to overcome.<\/p><h4><strong>Other Data Science Trends for 2020<\/strong><\/h4><p>Business leaders can use the\u00a0<a href=\"https:\/\/www.gartner.com\/smarterwithgartner\/gartner-top-10-data-analytics-trends\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">following trends<\/a> to set their business and data-technology priorities; these are predicted to have a disruptive business impact in the next three to five years:<\/p><ul><li><strong>Augmented Analytics:<\/strong> Major business analytics vendors will incorporate augmented analytics into their solutions by 2020 to provide a market differentiation between themselves and their competitors. The rapid adoption of cloud computing and the growth of IoT and connected devices are major drivers of augmented analytics. Many business clients may prefer augmented analytics over traditional analytics to reduce human errors and bias.<\/li><\/ul><ul><li><strong>Natural Language Processing (NLP) and Conversational Analytics:<\/strong>\u00a0As data and analytics jointly drive the current customer experience, talent management system, supply chains, or financial operations,\u00a0<a href=\"http:\/\/www.informationweek.com\/big-data\/ai-machine-learning\/10-data-and-analytics-trends-for-2020\/d\/d-id\/1336310\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">NLP and conversational analytics<\/a>\u00a0will complement augmented analytics in 2020. Find additional information in\u00a0<em><a href=\"https:\/\/www.dataversity.net\/future-nlp-data-science\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">The Future of NLP in Data Science<\/a>.<\/em><\/li><\/ul><ul><li><strong>Continuous Intelligence:<\/strong> Starting in 2020, more than 50 per cent of emerging business solutions will \u201cincorporate continuous intelligence,\u201d which utilizes real-time data to guide business decisions.<\/li><li><strong>Automation of Data Management:<\/strong> With the sudden exponential growth of data and short supply of skilled data-technology experts, enterprises are increasingly demanding automated Data Science and business analytics platforms. In 2020, over 40<a href=\"https:\/\/www.gartner.com\/en\/documents\/3746424\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">\u00a0<\/a>per cent\u00a0of Data Science tasks will be automated, thanks to the rapid integration of ML in Data Science platforms.<\/li><li><strong>Graph Databases:<\/strong>\u00a0<a href=\"https:\/\/www.dataversity.net\/the-third-generation-of-graph-databases\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">Graph databases<\/a>\u00a0and graph processing will be used at an accelerated pace in the \u201cnext few years\u201d to enable adaptive Data Science. Graph databases have the capability to store both structured and unstructured data and even a combination of them.<\/li><li><strong>Data Fabric:<\/strong>\u00a0The\u00a0<a href=\"https:\/\/www.dataversity.net\/the-data-fabric-an-innovative-data-management-solution\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">data fabric<\/a>\u00a0helps in building the \u201cbusiness context\u201d of data, thereby making the meaning of the data comprehensible to the users. The data fabric, conceptually, supports all enterprise data. The data fabric can also be designed to provide \u201creusable data services, pipelines, semantic tiers, or APIs\u201d through blended data- integration approaches.<\/li><li><strong>Autonomous Things:<\/strong>\u00a0This technology indicates the use of physical devices with highly automated (AI-enabled) features to reduce human intervention. In traditional systems, these functions were generally performed by humans.<\/li><\/ul><p>With the\u00a0<a href=\"https:\/\/www.caprivacy.org\/\" target=\"_blank\" rel=\"noreferrer noopener\" aria-label=\" (opens in a new tab)\">California Consumer Privacy Act<\/a>\u00a0(CCPA) put into practice in 2020, data scientists and data analysts will need to become familiar with and knowledgeable about CCPA and other related data regulations impacting data processes. Thus, Data Governance will gain more importance in Data Science practices in 2020.<\/p><\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Source: dataversity The exponential growth of data, partly generated by sensor-driven devices, is making Data Science and machine learning (ML) market differentiators in global business-analytics solutions. With the rising demand in\u00a0Data Science\u00a0and ML skills, 2020 may well be a witness to several new trends in the field. According to IDC: \u201c[I]f our digital universe or<\/p>\n","protected":false},"author":1,"featured_media":3778,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[220],"class_list":["post-3777","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","tag-automation"],"aioseo_notices":[],"jetpack_sharing_enabled":true,"jetpack_featured_media_url":"https:\/\/icaninfotech.com\/wp-content\/uploads\/2020\/03\/ds8.jpeg","_links":{"self":[{"href":"https:\/\/icaninfotech.com\/wp-json\/wp\/v2\/posts\/3777","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icaninfotech.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/icaninfotech.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/icaninfotech.com\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/icaninfotech.com\/wp-json\/wp\/v2\/comments?post=3777"}],"version-history":[{"count":0,"href":"https:\/\/icaninfotech.com\/wp-json\/wp\/v2\/posts\/3777\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/icaninfotech.com\/wp-json\/wp\/v2\/media\/3778"}],"wp:attachment":[{"href":"https:\/\/icaninfotech.com\/wp-json\/wp\/v2\/media?parent=3777"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/icaninfotech.com\/wp-json\/wp\/v2\/categories?post=3777"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/icaninfotech.com\/wp-json\/wp\/v2\/tags?post=3777"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}