{"id":15707,"date":"2022-09-14T16:53:35","date_gmt":"2022-09-14T22:53:35","guid":{"rendered":"http:\/\/www.designandexecute.com\/designs\/?p=15707"},"modified":"2022-09-19T21:16:23","modified_gmt":"2022-09-20T03:16:23","slug":"what-is-the-difference-between-a-data-engineer-an-analytic-engineer-and-a-bi-engineer-how-does-the-data-scientist-compare","status":"publish","type":"post","link":"https:\/\/www.designandexecute.com\/designs\/what-is-the-difference-between-a-data-engineer-an-analytic-engineer-and-a-bi-engineer-how-does-the-data-scientist-compare\/","title":{"rendered":"What is the difference between a data engineer, an analytic engineer, and a BI engineer? How does the Data Scientist compare?"},"content":{"rendered":"\n<p>I wrote this article years ago, and now there are names for engineers focusing on a segment of the data value chain.<\/p>\n\n\n\n<figure class=\"wp-block-embed-wordpress wp-block-embed is-type-wp-embed is-provider-design-and-execute\"><div class=\"wp-block-embed__wrapper\">\n<blockquote class=\"wp-embedded-content\" data-secret=\"2yu4wzcD27\"><a href=\"https:\/\/www.designandexecute.com\/designs\/where-to-put-the-business-calculation-rules-in-data-warehousing\/\">Where to put the Business Calculation Rules in Data Warehousing?<\/a><\/blockquote><iframe loading=\"lazy\" class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; clip: rect(1px, 1px, 1px, 1px);\" title=\"&#8220;Where to put the Business Calculation Rules in Data Warehousing?&#8221; &#8212; Design and Execute\" src=\"https:\/\/www.designandexecute.com\/designs\/where-to-put-the-business-calculation-rules-in-data-warehousing\/embed\/#?secret=2yu4wzcD27\" data-secret=\"2yu4wzcD27\" width=\"600\" height=\"338\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe>\n<\/div><\/figure>\n\n\n\n<p><strong>You are a data engineer<\/strong> if you focus on combining data sources, building data pipelines, and data modeling.  You must love data integration and number crunching.<\/p>\n\n\n\n<p><strong>You are an analytic engineer<\/strong> if you focus on creating aggregate data stores that match Key Performance Indicators (KPI).  These metrics Operational Data Stores (ODS) deliver ROLAP analytics, &#8220;drill through&#8221;  and &#8220;drill down&#8221; insightful solutions.<\/p>\n\n\n\n<figure class=\"wp-block-embed-wordpress wp-block-embed is-type-wp-embed is-provider-design-and-execute\"><div class=\"wp-block-embed__wrapper\">\n<blockquote class=\"wp-embedded-content\" data-secret=\"wOrbQjNXrx\"><a href=\"https:\/\/www.designandexecute.com\/designs\/holy-trinity-of-analytics\/\">Holy Trinity of Analytics<\/a><\/blockquote><iframe loading=\"lazy\" class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; clip: rect(1px, 1px, 1px, 1px);\" title=\"&#8220;Holy Trinity of Analytics&#8221; &#8212; Design and Execute\" src=\"https:\/\/www.designandexecute.com\/designs\/holy-trinity-of-analytics\/embed\/#?secret=wOrbQjNXrx\" data-secret=\"wOrbQjNXrx\" width=\"600\" height=\"338\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe>\n<\/div><\/figure>\n\n\n\n<p> <strong>You are a Business Intelligence (BI) engineer<\/strong> if you focus on BI tools to create custom and pixel-perfect dashboards, analytic drill paths, and securely delivered parameterized reports.  These BI engineers are designers that understand human psychology, storytelling, and human interpretation.  You marry design skills with expertise in a BI tool of choice to solve business problems.  The BI engineer and the Data Analyst role have a ton of overlap in this regard.<\/p>\n\n\n\n<p><strong>You are a Data Scientist <\/strong>if you are a stats<strong> <\/strong>person, a tech-savvy data wizard combined with an industry Subject Matter Expert (SME).  The role expects you to take on all functions of both developer and designer.  The data scientist must see both the forest and the trees.<\/p>\n\n\n\n<p>The main difference between the engineer and the scientist is the engineer does not need to know about statistics, but the scientist must know about  <strong>Ensemble methods<\/strong>, <strong>OverFitting, and UnderFitting methods,<\/strong> for example, to do machine learning. (ML) and to power artificial intelligence (AI).<\/p>\n\n\n\n<figure class=\"wp-block-embed-wordpress wp-block-embed is-type-wp-embed is-provider-design-and-execute\"><div class=\"wp-block-embed__wrapper\">\n<blockquote class=\"wp-embedded-content\" data-secret=\"1q5mvsXGu9\"><a href=\"https:\/\/www.designandexecute.com\/designs\/machine-learning-terms-every-data-scientist-should-know\/\">Machine Learning Terms Every Data Scientist Should Know<\/a><\/blockquote><iframe loading=\"lazy\" class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; clip: rect(1px, 1px, 1px, 1px);\" title=\"&#8220;Machine Learning Terms Every Data Scientist Should Know&#8221; &#8212; Design and Execute\" src=\"https:\/\/www.designandexecute.com\/designs\/machine-learning-terms-every-data-scientist-should-know\/embed\/#?secret=1q5mvsXGu9\" data-secret=\"1q5mvsXGu9\" width=\"600\" height=\"338\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe>\n<\/div><\/figure>\n\n\n\n<p>Data scientists are an x-functional group to work in parallel as SMEs, data integrators, and number crunchers to crunch large datasets, develop statistical models, and deploy them to make predictions based on data.  The development of these models using training data is a machine learning (ML) process.<\/p>\n\n\n\n<p>Scientists can define the mathematical rules governing knowledge development and discrete facts&#8217; regular dissolution.<\/p>\n\n\n\n<p>Neuroscientist Richard Restak, who writes about the power of the limbic system in The Naked Brain, says that when people are forced to make decisions based on data alone, they take more time and usually overanalyze the situation. <\/p>\n\n\n\n<p>The naked truth is that we must bring in experts but pair them with people who know your business.  Find designers, developers, and data scientists, but also include behavioral scientists and people who understand emerging technologies and how they might affect your industry.  A team is always more potent than a superstar.<\/p>\n\n\n\n<figure class=\"wp-block-embed-wordpress wp-block-embed is-type-wp-embed is-provider-design-and-execute\"><div class=\"wp-block-embed__wrapper\">\n<blockquote class=\"wp-embedded-content\" data-secret=\"FoAtLRMraN\"><a href=\"https:\/\/www.designandexecute.com\/designs\/stimulative-analysis-is-much-better-way-to-approach-the-subject-of-predictive\/\">Simulative Analysis is much better way to Approach the subject of Predictive<\/a><\/blockquote><iframe loading=\"lazy\" class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; clip: rect(1px, 1px, 1px, 1px);\" title=\"&#8220;Simulative Analysis is much better way to Approach the subject of Predictive&#8221; &#8212; Design and Execute\" src=\"https:\/\/www.designandexecute.com\/designs\/stimulative-analysis-is-much-better-way-to-approach-the-subject-of-predictive\/embed\/#?secret=FoAtLRMraN\" data-secret=\"FoAtLRMraN\" width=\"600\" height=\"338\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe>\n<\/div><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>I wrote this article years ago, and now there are names for engineers focusing on a segment of the data value chain. You are a data engineer if you focus on combining data sources, building data pipelines, and data modeling. You must love data integration and number crunching. You are an analytic engineer if you [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":15711,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[32,31],"tags":[],"class_list":["post-15707","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-bi-dashboards-analytics","category-bi-data-warehouse"],"jetpack_featured_media_url":"https:\/\/www.designandexecute.com\/designs\/wp-content\/uploads\/2022\/09\/Data-Engineer.jpg","_links":{"self":[{"href":"https:\/\/www.designandexecute.com\/designs\/wp-json\/wp\/v2\/posts\/15707","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.designandexecute.com\/designs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.designandexecute.com\/designs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.designandexecute.com\/designs\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.designandexecute.com\/designs\/wp-json\/wp\/v2\/comments?post=15707"}],"version-history":[{"count":5,"href":"https:\/\/www.designandexecute.com\/designs\/wp-json\/wp\/v2\/posts\/15707\/revisions"}],"predecessor-version":[{"id":15894,"href":"https:\/\/www.designandexecute.com\/designs\/wp-json\/wp\/v2\/posts\/15707\/revisions\/15894"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.designandexecute.com\/designs\/wp-json\/wp\/v2\/media\/15711"}],"wp:attachment":[{"href":"https:\/\/www.designandexecute.com\/designs\/wp-json\/wp\/v2\/media?parent=15707"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.designandexecute.com\/designs\/wp-json\/wp\/v2\/categories?post=15707"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.designandexecute.com\/designs\/wp-json\/wp\/v2\/tags?post=15707"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}