{"id":38402,"date":"2025-05-10T01:39:31","date_gmt":"2025-05-10T05:39:31","guid":{"rendered":"https:\/\/statanalytica.com\/blog\/?p=38402"},"modified":"2025-05-10T01:40:47","modified_gmt":"2025-05-10T05:40:47","slug":"data-science-vs-data-analytics","status":"publish","type":"post","link":"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/","title":{"rendered":"Data Science Vs Data Analytics: Which One To Choose?"},"content":{"rendered":"\n<p>When it comes to the world of data, the terms data science vs data analytics often confuse a lot of people, and it\u2019s easy to see why. Both fields deal with data, both help businesses make smart decisions, and both are in high demand. But here\u2019s the thing: they\u2019re not the same. In fact, understanding the difference between the two can help you choose the right career path, build the right team, or make better sense of tech talk around you.<\/p>\n\n\n\n<p>Imagine Data Science as the field that builds smart systems, predicts the future using machine learning, and digs deep into big data. On the other hand, Data Analytics is more focused on looking at current data, spotting trends, and answering specific business questions.<\/p>\n\n\n\n<p>If you\u2019ve ever wondered which one does what or which one is right for you, this blog is here to clarify things as easily as possible. Let\u2019s explore the main differences between data science vs data analytics, clearing up any confusion.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"what-is-data-science\"><\/span>What is Data Science?<span class=\"ez-toc-section-end\"><\/span><\/h2><div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-light-blue ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-69f48dfcc265c\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #ff5104;color:#ff5104\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #ff5104;color:#ff5104\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-69f48dfcc265c\" checked aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#what-is-data-science\" >What is Data Science?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#what-is-data-analytics\" >What is Data Analytics?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#data-science-vs-data-analytics-side-by-side-comparison\" >Data Science vs Data Analytics: Side-by-Side Comparison<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#data-science-vs-data-analytics-key-differences\" >Data Science vs Data Analytics: Key Differences<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#1-goal-purpose\" >1. Goal &amp; Purpose<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#2-data-handling\" >2. Data Handling<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#3-skills-and-techniques\" >3. Skills and Techniques<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#4-outcomes\" >4. Outcomes<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#5-career-roles\" >5. Career Roles<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#data-science-vs-data-analytics-which-one-should-you-choose\" >Data Science vs Data Analytics: Which One Should You Choose?<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#choose-data-science-if%e2%80%a6\" >Choose Data Science if\u2026<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#choose-data-analytics-if%e2%80%a6\" >Choose Data Analytics if\u2026<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#conclusion\" >Conclusion<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#faqs\" >FAQs<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#can-a-data-analyst-become-a-data-scientist\" >Can a data analyst become a data scientist?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#which-has-better-career-growth-data-science-or-data-analytics\" >Which has better career growth: data science or data analytics?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/statanalytica.com\/blog\/data-science-vs-data-analytics\/#do-both-fields-require-coding\" >Do both fields require coding?<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n\n\n\n\n<p>Data Science revolves around leveraging data to gain insights into the world and make informed decisions. It\u2019s a powerful mix of statistics, <a href=\"https:\/\/statanalytica.com\/blog\/computer-science-project-ideas\/\" target=\"_blank\" rel=\"noreferrer noopener\">computer science<\/a>, and domain knowledge that helps turn raw information into meaningful insights.<\/p>\n\n\n\n<p>Think of it this way \u2014 every time you get a product recommendation on Amazon, see personalized content on Netflix, or use Google Maps to avoid traffic, that\u2019s Data Science working behind the scenes. It collects massive amounts of data, cleans it, analyzes patterns, builds predictive models, and helps businesses (and even you) make better choices.<\/p>\n\n\n\n<p>Methods and tools such as machine learning, artificial intelligence, data mining, and predictive analytics are central to data science. Data scientists use programming languages like Python or R and tools like Jupyter Notebook, TensorFlow, and SQL to handle and process huge datasets.<\/p>\n\n\n\n<p>But it\u2019s not just about technical skills \u2014 data scientists also need to be good problem-solvers and critical thinkers. Their job is to ask the right questions, dig deep into the data, and tell a story that others can understand and act on.<\/p>\n\n\n\n<p>In short, Data Science is the art and science of turning data into decisions \u2014 whether it\u2019s predicting what customers will buy next or helping doctors detect diseases early.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"what-is-data-analytics\"><\/span>What is Data Analytics?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Data Analytics is all about making sense of existing data to solve real-world problems and improve decision-making. While Data Science often deals with predicting the future, Data Analytics focuses more on understanding the present and the past.<\/p>\n\n\n\n<p>Let\u2019s say a company wants to know why sales dropped last month, which marketing campaign worked best, or what products are performing well \u2014 that\u2019s where data analytics comes in. It helps answer questions like \u201cWhat happened?\u201d, \u201cWhy did it happen?\u201d, and \u201cWhat can we do about it?\u201d<\/p>\n\n\n\n<p>Data analysts collect, organize, and examine structured data (like numbers and stats in spreadsheets or databases) to find patterns, trends, and useful insights. They use tools like Excel, SQL, Tableau, Power BI, and sometimes programming languages like Python or R to clean data, create visual reports, and support business decisions.<\/p>\n\n\n\n<p>In simple terms, Data Analytics turns raw numbers into clear, actionable insights. It helps businesses reduce costs, improve performance, and better understand their customers.<\/p>\n\n\n\n<p>Whether tracking website traffic, analyzing customer behavior, or evaluating company performance, data analytics plays a crucial role in helping organizations stay informed and ahead of the competition.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"data-science-vs-data-analytics-side-by-side-comparison\"><\/span>Data Science vs Data Analytics: Side-by-Side Comparison<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Now that we\u2019ve explored Data Science and Data Analytics individually, let\u2019s compare them side by side to really understand how they differ and where they overlap. Mentioned below is a simple breakdown that shows how the two fields stack up:-<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td><strong>Aspect<\/strong><\/td><td><strong>Data Science<\/strong><\/td><td><strong>Data Analytics<\/strong><\/td><\/tr><tr><td><strong>Primary Focus<\/strong><\/td><td>Predicting future outcomes and building models<\/td><td>Analyzing historical and current data to uncover trends and insights.<\/td><\/tr><tr><td><strong>Goal<\/strong><\/td><td>Uncover hidden patterns, predict future outcomes, and tackle complex problems by analyzing data.<\/td><td>Answer specific business questions and support decision-making.<\/td><\/tr><tr><td><strong>Type of Data<\/strong><\/td><td>Works with both structured and unstructured data (e.g., images, videos, text, etc.)<\/td><td>Mostly structured data (like databases, spreadsheets)<\/td><\/tr><tr><td><strong>Techniques Used<\/strong><\/td><td>Machine learning, AI, data modeling, deep learning<\/td><td>Data cleaning, visualization, statistical analysis, and reporting<\/td><\/tr><tr><td><strong>Common Tools<\/strong><\/td><td>Python, R, TensorFlow, Hadoop, SQL<\/td><td>Excel, SQL, Tableau, Power BI, and Google Data Studio are commonly used tools.<\/td><\/tr><tr><td><strong>End Result<\/strong><\/td><td>Predictive models, data products, recommendations, and automation<\/td><td>Dashboards, reports, insights, and data visualizations<\/td><\/tr><tr><td><strong>Who Uses It?<\/strong><\/td><td>Data scientists, AI\/ML engineers, and research teams<\/td><td>Business analysts, data analysts, marketing teams, and decision-makers<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>Although both fields are data-driven, they differ in their objectives, approaches, and results. You can think of Data Science as the research and innovation department, while Data Analytics serves as the engine for business action and insights.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"data-science-vs-data-analytics-key-differences\"><\/span>Data Science vs Data Analytics: Key Differences<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>While Data Science and Data Analytics may sound similar and even overlap in some areas, they are quite different in terms of goals, tools, and the type of work they involve. Understanding these key differences can help you decide which path suits your interests or which role your business really needs. Mentioned below are some of the key differences to keep in mind:-<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"1-goal-purpose\"><\/span>1. Goal &amp; Purpose<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Data Science is all about building models, making predictions, and uncovering hidden patterns in large, often messy datasets. It\u2019s utilized to respond to questions like \u201cWhat will happen next?\u201d or \u201cCan we automate this task using data?\u201d<\/li>\n\n\n\n<li>In contrast, Data Analytics is centered around extracting valuable insights from existing data. It answers questions like \u201cWhat happened?\u201d and \u201cWhy did it happen?\u201d, helping businesses improve their current performance.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"2-data-handling\"><\/span>2. Data Handling<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Data Scientists frequently handle both structured and unstructured data, such as text, images, and audio, while managing large volumes of information from diverse sources.<\/li>\n\n\n\n<li>Data Analysts usually work with structured data \u2014 the kind you\u2019d find in spreadsheets or databases \u2014 to clean, organize, and analyze it.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"3-skills-and-techniques\"><\/span>3. Skills and Techniques<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Data Science involves heavy use of machine learning, deep learning, advanced statistics, and programming (commonly Python or R).<\/li>\n\n\n\n<li>Data Analytics leans more toward data visualization, descriptive statistics, and business intelligence tools like Excel, Tableau, or Power BI.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"4-outcomes\"><\/span>4. Outcomes<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The outcome of data science is typically a predictive model, algorithm, or intelligent system \u2014 something that automates or enhances decision-making.<\/li>\n\n\n\n<li>The outcome of data analytics is usually insights, reports, and visual dashboards that guide business strategies and actions.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"5-career-roles\"><\/span>5. Career Roles<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Common roles in data science include Data Scientist, Machine Learning Engineer, and AI Specialist.<\/li>\n\n\n\n<li>In data analytics, roles include Data Analyst, Business Analyst, and Reporting Analyst.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"data-science-vs-data-analytics-which-one-should-you-choose\"><\/span>Data Science vs Data Analytics: Which One Should You Choose?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>If you\u2019re trying to decide between a career in data science or data analytics, the answer really depends on your interests, goals, and the kind of work you enjoy doing.<\/p>\n\n\n\n<p>Let\u2019s break it down to help you choose the right path:<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"choose-data-science-if%e2%80%a6\"><\/span>Choose Data Science if\u2026<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>You love solving complex problems and thinking several steps ahead.<\/li>\n\n\n\n<li>You\u2019re interested in machine learning, artificial intelligence, or building predictive models.<\/li>\n\n\n\n<li>You\u2019re comfortable with programming languages like Python or R and enjoy working with large, messy datasets.<\/li>\n\n\n\n<li>You want to work on cutting-edge technologies and help build smart systems that can automate or improve future decision-making.<\/li>\n<\/ul>\n\n\n\n<p>A career in data science is more technical, research-oriented, and future-focused. It\u2019s great for people who enjoy math, coding, and working with data at a deep level.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"choose-data-analytics-if%e2%80%a6\"><\/span>Choose Data Analytics if\u2026<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>You enjoy analyzing trends, creating reports, and helping businesses make smarter choices.<\/li>\n\n\n\n<li>You\u2019re interested in using data to solve real-world business problems and improve performance.<\/li>\n\n\n\n<li>You like working with tools like Excel, SQL, Tableau, or Power BI.<\/li>\n\n\n\n<li>You prefer structured tasks and delivering insights that teams can use right away.<\/li>\n<\/ul>\n\n\n\n<p>Data analytics is perfect for those who want to analyze data to understand what\u2019s happening now and why, and help guide practical business decisions.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"conclusion\"><\/span>Conclusion<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In the battle of Data Science vs Data Analytics, there\u2019s no clear winner \u2014 it all comes down to what you want to achieve with data. Whether you&#8217;re drawn to the idea of building predictive models and diving into AI, or you\u2019re more interested in analyzing trends and helping businesses make smarter decisions, both paths offer incredible opportunities.<\/p>\n\n\n\n<p>So, take some time to think about your skills, interests, and <a href=\"https:\/\/en.wikipedia.org\/wiki\/Career\" target=\"_blank\" rel=\"noreferrer noopener\">career goals<\/a>. Are you ready to explore the future of technology with Data Science, or do you want to make an immediate impact with Data Analytics? Whichever path you choose, know that both fields are at the heart of today\u2019s data-driven world, offering a chance to shape the future.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"faqs\"><\/span>FAQs<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<div id=\"rank-math-faq\" class=\"rank-math-block\">\n<div class=\"rank-math-list \">\n<div id=\"faq-question-1746855144972\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><span class=\"ez-toc-section\" id=\"can-a-data-analyst-become-a-data-scientist\"><\/span>Can a data analyst become a data scientist?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Yes. With additional training in machine learning, programming, and statistics, a data analyst can transition into a data scientist role.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1746855149884\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><span class=\"ez-toc-section\" id=\"which-has-better-career-growth-data-science-or-data-analytics\"><\/span>Which has better career growth: data science or data analytics?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Both offer strong career opportunities, but data science often provides higher salaries and growth due to its complexity and demand in cutting-edge industries.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1746855151449\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><span class=\"ez-toc-section\" id=\"do-both-fields-require-coding\"><\/span>Do both fields require coding?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Yes, but the level differs. Data science requires in-depth coding knowledge (Python, R), while data analytics may only need basic SQL or scripting and focus more on visualization tools.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>When it comes to the world of data, the terms data science vs data analytics often confuse a lot of people, and it\u2019s easy to see why. Both fields deal with data, both help businesses make smart decisions, and both are in high demand. But here\u2019s the thing: they\u2019re not the same. In fact, understanding [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":38404,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"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":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[139,77],"tags":[5462],"class_list":["post-38402","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-analytics","category-data-science","tag-data-science-vs-data-analytics"],"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/posts\/38402","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/comments?post=38402"}],"version-history":[{"count":3,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/posts\/38402\/revisions"}],"predecessor-version":[{"id":38408,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/posts\/38402\/revisions\/38408"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/media\/38404"}],"wp:attachment":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/media?parent=38402"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/categories?post=38402"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/tags?post=38402"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}