{"id":597,"date":"2014-09-26T06:04:36","date_gmt":"2014-09-26T00:34:36","guid":{"rendered":"https:\/\/www.mygreatlearning.com\/blog\/transition-from-business-intelligence-to-web-analytics-role-perspective\/"},"modified":"2024-09-30T21:13:17","modified_gmt":"2024-09-30T15:43:17","slug":"transition-from-business-intelligence-to-web-analytics-role-perspective","status":"publish","type":"post","link":"https:\/\/www.mygreatlearning.com\/blog\/transition-from-business-intelligence-to-web-analytics-role-perspective\/","title":{"rendered":"Transition from Business Intelligence to Web Analytics: Role perspective"},"content":{"rendered":"<p><em><strong>Author:<\/strong> Akash Kapoor (Student,PGPBA Class of 2015, Great Lakes)<\/em><br \/>\nThe buzzword in IT industry today is SMAC. We will focus on \u2018A\u2019 of SMAC, the analytics. Analytics is in upward mode, more and more professionals are planning to jump into the analytics bandwagon. We keep reading about short supply of analytics professionals in the industry but how do we make a move to analytics. This article talks about one of the transitions - from Business Intelligence to Analytics that too Web Analytics. Why did I choose Web Analytics? The reason is because there is lot of demand for Analytics and within the umbrella of Analytics, web analytics seems to be most in demand.<br \/>\nIt is assumed that a person in Business Intelligence is already passionate about data. Web analytics is all about data. There are several roles in Business Intelligence which are common with Web Analytics too. Just keep in mind when we are saying Business Intelligence, it is the contemporary Business Intelligence with Big Data technology. It has structured as well as unstructured data.<\/p>\n<div class=\"ast-oembed-container \" style=\"height: 100%;\"><iframe title=\"Why Should you Learn Analytics Now? | Great learning\" width=\"500\" height=\"281\" src=\"https:\/\/www.youtube.com\/embed\/HQXWbsg8gJ8?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/div>\n<p>Web Analytics too has the similar architecture to that of contemporary Business Intelligence, where we link the web data from say e-commerce website with the structural data from data warehouse. The common roles in both the verticals are Architect, ETL developer, Tester (to some extent), Report writer. Business Analyst in BI would be different from Web Analytics. In addition to these roles, data scientist is a new role in web analytics domain. Candidates making a shift have different questions in mind. We will explore some of them.<br \/>\n<strong>How do I present myself during the job discussion for Web Analytics domain?<\/strong><br \/>\nArchitects and ETL developers may find it like another BI discussion, as pretty much all the components are the same \u2013 extracting data from structured and unstructured data sources, loading it in big data cluster. Aggregation and then with ETL tools loading it in data marts, this could be one of the pipelines.<br \/>\nBusiness Analyst in BI is responsible for gathering reporting requirements and then pretty much testing it in UAT phase. Web Analytics business analyst would require prior knowledge of web domain as to what to look for like clickstreams, bounce rate etc. This data may be combined with the customer data to provide business insights. In a discussion for this role, a BI business analyst has to learn more about web domain and interpreting the results from analysis of data.<br \/>\nData scientist is a new role for professionals in business intelligence industry; in fact this was a new role for everyone till not long ago. This role would require maximum effort compared to the roles discussed above. Before applying for this role, one needs to learn statistical methods. There are several training institutes which provide training in statistical methods on different analysis tools like SAS, R to name the few. There are also tools dedicated to web analytics like Omniture, which has been acquired by Adobe. Also, one should solve few case studies to get a hang of the web analytics industry. If a person has got prior experience in any analysis tool (could be during higher studies) or has a written a thesis with quantitative data analysis, that should be spoken during the discussion.<br \/>\n<strong>Will my prior experience be considered?<\/strong><br \/>\nIn case of architects and ETL developers, all of it will be considered. Testing experience too would be considered because once the analytical model is ready it will be implemented and a report would be generated which needs to be tested by the testers that is same as business intelligence.<br \/>\nBusiness Analysts experience will be considered in a way that one brings a thought process along with him\/her eg. For a product company, how much of a particular product was sold in a particular region in first quarter of 2014. Since a BI business analyst comes with this mind set, the transition would be easier, just that one needs to broaden the horizon a bit eg. How much of a particular product was bought by customers coming from xyz website in first quarter of 2014.The experience would be counted, if you are able to relate it as mentioned above.<br \/>\nData scientist role would require training, cracking few case studies, prior experience from college with thesis or any analysis tool.<br \/>\n<strong>How long does it take to get a break in web analytics?<\/strong><br \/>\nIn all the roles discussed above, the most effort consuming transition for BI professionals is to become a data scientist. To be honest this is the role which is most in demand. Give it a good 3 to 6 months.&nbsp; Rest of the roles would be easier to get a break into. Business analysts too would require reading the literature as to what kind of reports companies look for, from web analytics.<br \/>\n<strong>Next steps<\/strong><br \/>\nJoin a course in data analytics (Architects and ETL developers, join this only if planning to be a data scientist)<br \/>\nSubscribe to web analytics blogs, communities<br \/>\nBe a part of web analytics groups on linkedin<br \/>\nI hope the article will help BI professionals transition into web analytics. In fact, it can also be generalized to other analytics verticals. Another reason of choosing web analytics was that it cuts across the board, it is a horizontal and would be much more in demand in future. In the next article we will look at this transition from technical prespective.<br \/>\n[optin-monster-shortcode id=\"squxepvugkce4cquclwn\"]<br \/>\n<strong>About the author:<\/strong><\/p>\n<p style=\"text-align: left\">Akash Kapoor is an experienced IT professional with almost 2 decades of work experience and more than 8 years in Business Intelligence with a distinction of leading Business Intelligence for world's largest biometric project- Aadhar, led BI initiatives in different geographies in several BI tools.&nbsp;Akash is a current student of Great Lakes PGPBA program.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Author: Akash Kapoor (Student,PGPBA Class of 2015, Great Lakes) The buzzword in IT industry today is SMAC. We will focus on \u2018A\u2019 of SMAC, the analytics. Analytics is in upward mode, more and more professionals are planning to jump into the analytics bandwagon. We keep reading about short supply of analytics professionals in the industry [&hellip;]<\/p>\n","protected":false},"author":41,"featured_media":860,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[5],"tags":[36777],"content_type":[],"class_list":["post-597","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-success-stories","tag-data-science-success-story"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.3 (Yoast SEO v27.3) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Transition from Business Intelligence to Web Analytics<\/title>\n<meta name=\"description\" content=\"In all the roles discussed above, the most effort consuming transition for Business Intelligence professionals is to become a data scientist.\" \/>\n<meta name=\"robots\" content=\"noindex, follow\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" 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