{"id":64507,"date":"2018-04-16T07:56:20","date_gmt":"2018-04-16T07:56:20","guid":{"rendered":"https:\/\/www.whizlabs.com\/?p=64507"},"modified":"2024-05-17T09:44:14","modified_gmt":"2024-05-17T04:14:14","slug":"hadoop-predictive-analytics","status":"publish","type":"post","link":"https:\/\/www.whizlabs.com\/blog\/hadoop-predictive-analytics\/","title":{"rendered":"How can Hadoop Help a Data Scientist in Predictive Analysis?"},"content":{"rendered":"<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Big Data Analytics has obtained a new height with Hadoop. This open source big data processing platform helps in capturing, storing, and processing the massive volumes of unstructured data. The real-time data has gained enormous credibility with its revolutionary contribution in business.\u00a0<\/span><span lang=\"EN-GB\">Hadoop predictive analytics is today&#8217;s real-time recommendation to reduce cost and market analysis for better performance.<\/span><\/p>\n<blockquote>\n<p style=\"text-align: justify;\">Want to get one level up in your Hadoop career? Here is the list of\u00a0<a href=\"https:\/\/www.whizlabs.com\/blog\/best-hadoop-certification-in-2018\/\" target=\"_blank\" rel=\"noopener\">Best Hadoop Certifications in 2018.\u00a0<\/a><span lang=\"EN-GB\">Choose one and get certified now!<\/span><\/p>\n<\/blockquote>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Hadoop predictive analytics is the advanced analytics method that provides better insights on the customer, potential risks, product portfolio in the market. Overall it is a competitive advantage for an organization in:<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li><span lang=\"EN-GB\">Detecting fraud<\/span><\/li>\n<li><span lang=\"EN-GB\">Optimizing marketing campaigns<\/span><\/li>\n<li><span lang=\"EN-GB\">Improving operations<\/span><\/li>\n<li><span lang=\"EN-GB\">Reducing risk<\/span><b><\/b><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Using Hadoop, data scientists can efficiently perform predictive analysis. Almost all business verticals like Finance, Banks, Retail, Energy, Health, Manufacturing, and Government use predictive analytics.<\/span><\/p>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">However, to know how does it happen and what is the Hadoop&#8217;s exact role in it, let&#8217;s move to the next section of the blog.<\/span><\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_76 ez-toc-wrap-left counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #ea7e02;color:#ea7e02\" 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: #ea7e02;color:#ea7e02\" 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><\/span><\/a><\/span><\/div>\n<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:\/\/www.whizlabs.com\/blog\/hadoop-predictive-analytics\/#What_is_Predictive_Analytics_Model\" >What is Predictive Analytics Model?<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.whizlabs.com\/blog\/hadoop-predictive-analytics\/#1_Classification_Model\" >1. Classification Model<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.whizlabs.com\/blog\/hadoop-predictive-analytics\/#2_Regression_Model\" >2. Regression Model<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.whizlabs.com\/blog\/hadoop-predictive-analytics\/#Different_Stages_of_Predictive_Analytics_Life_Cycle\" >Different Stages of Predictive Analytics Life Cycle<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.whizlabs.com\/blog\/hadoop-predictive-analytics\/#Hadoop_and_Big_Data_Predictive_Analytics\" >Hadoop and Big Data Predictive Analytics<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.whizlabs.com\/blog\/hadoop-predictive-analytics\/#Hadoop_Challenges_for_Big_Data_Analytics\" >Hadoop Challenges for Big Data Analytics<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.whizlabs.com\/blog\/hadoop-predictive-analytics\/#Conclusion\" >Conclusion<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"What_is_Predictive_Analytics_Model\"><\/span><b><span lang=\"EN-GB\">What is Predictive Analytics Model?<\/span><\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">In predictive analysis model, data scientists use input data and its significance through different statistical method to define an outcome or probability of the output data. The output data is commonly known as the target model. <\/span><\/p>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">There are two types of models followed by predictive analytics:<\/span><\/p>\n<h3 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"1_Classification_Model\"><\/span>1. Classification Model<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span lang=\"EN-GB\">The classification model for predictive analysis predicts class membership. For example, through this model, a data scientist can predict whether a member of a group will leave or retain. It is a logical representation and usually represents 0 or 1.<\/span><\/p>\n<h3><span class=\"ez-toc-section\" id=\"2_Regression_Model\"><\/span><span lang=\"EN-GB\">2. Regression Model <\/span><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span lang=\"EN-GB\">The regression model for predictive analysis predicts number through analysis. For example, how much revenue a business can obtain is easily analyzed using this model.<\/span><b><\/b><\/p>\n<p style=\"text-align: justify;\"><strong><span lang=\"EN-GB\">Popular predictive modeling techniques are:<\/span><\/strong><\/p>\n<ul style=\"text-align: justify;\">\n<li><span lang=\"EN-GB\">Decision trees<\/span><\/li>\n<li><span lang=\"EN-GB\">Regression (logistic and linear)<\/span><\/li>\n<li><span lang=\"EN-GB\">Neural networks<\/span><\/li>\n<li><span lang=\"EN-GB\">Bayesian analysis<\/span><\/li>\n<li><span lang=\"EN-GB\">Ensemble models<\/span><\/li>\n<li><span lang=\"EN-GB\">Gradient boosting<\/span><\/li>\n<li><span lang=\"EN-GB\">Partial least squares<\/span><\/li>\n<li><span lang=\"EN-GB\">Incremental response (also called net lift or uplift models)<\/span><\/li>\n<li><span lang=\"EN-GB\">K-nearest neighbor (knn)<\/span><\/li>\n<li><span lang=\"EN-GB\">Principal component analysis<\/span><\/li>\n<li><span lang=\"EN-GB\">Support vector machine<\/span><\/li>\n<li><span lang=\"EN-GB\">Memory-based reasoning<\/span><\/li>\n<li><span lang=\"EN-GB\">Time series data mining<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><strong><span lang=\"EN-GB\">Whatever models an organization follows two important factors should be taken are:<\/span><\/strong><\/p>\n<ol style=\"text-align: justify;\">\n<li><span lang=\"EN-GB\">A predictive analysis involves different in-house and external vendors to collaborate in the process. Hence, the intellectual property of the organization must remain safe.<\/span><\/li>\n<li><span lang=\"EN-GB\">Predictive analytics model used by the company must be up to date and keep pace with the ongoing changes in the market. Otherwise, the competitive advantage obtained by the model may become obsolete over the period of time.<\/span><\/li>\n<\/ol>\n<blockquote>\n<p style=\"text-align: justify;\"><em>Preparing for Hadoop interview? Here are the <a href=\"https:\/\/www.whizlabs.com\/blog\/best-hadoop-certification-in-2018\/\" target=\"_blank\" rel=\"noopener\">Top 50 Hadoop Interview Questions and Answers<\/a> that will help you crack the interview!<\/em><\/p>\n<\/blockquote>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Different_Stages_of_Predictive_Analytics_Life_Cycle\"><\/span><b><span lang=\"EN-GB\">Different Stages of Predictive Analytics Life Cycle<\/span><\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">The core of predictive analytics is following its life cycle. The predictive model goes through various stages of its lifecycle \u2013 starting from the problem statement that is its birth up to its replacement by another model. Followings are the s<\/span><span lang=\"EN-GB\">tages of predictive analytics:<\/span><\/p>\n<h4><a href=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2024\/05\/predictive-analytics-lifecycle.png\"><img decoding=\"async\" class=\"aligncenter wp-image-64516 size-full\" src=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2024\/05\/predictive-analytics-lifecycle.png\" alt=\"Predictive Analytics Life Cycle\" width=\"402\" height=\"319\" \/><\/a><b><span lang=\"EN-GB\">1. Identifying the Problem<\/span><\/b><\/h4>\n<ul style=\"text-align: justify;\">\n<li>This is the very first step to have an understanding of the problem.<\/li>\n<li>Need a dry run on the predictive analytics steps to solve the problem.<\/li>\n<li>To set the goal of the analysis, i.e. what would be the target model based on the input data.<\/li>\n<\/ul>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">2. Designing the Required Data<\/span><\/b><\/h4>\n<ul style=\"text-align: justify;\">\n<li><span lang=\"EN-GB\">To consider the useful predictions based on input data.<\/span><\/li>\n<li><span lang=\"EN-GB\">To define decision model using the insights obtained by analysis<\/span><\/li>\n<li><span lang=\"EN-GB\">To follow necessary actions based on the analysis.<\/span><\/li>\n<\/ul>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">3. Pre-processing of Data<\/span><\/b><\/h4>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">It is the most time-consuming phase of the entire cycle.<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li><span lang=\"EN-GB\">Analysis needs data from various sources like sensors, transactional system, logs, etc.<\/span><\/li>\n<li><span lang=\"EN-GB\">The collected data may be unformatted which needs data management which means cleanse up and preparing them for analysis.<\/span><\/li>\n<li><span lang=\"EN-GB\">Data preparation involves analysis of business problems too.<\/span><\/li>\n<\/ul>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">4. Performing Analytics Over Data<\/span><\/b><\/h4>\n<ul style=\"text-align: justify;\">\n<li><span lang=\"EN-GB\">This is the beginning stage of predictive analytics model.<\/span><\/li>\n<li><span lang=\"EN-GB\">Either data analytics tools or manual effort is involved in this step.<\/span><\/li>\n<li><span lang=\"EN-GB\">Deployment of the model which means the model starts working on prepared data.<\/span><\/li>\n<li><span lang=\"EN-GB\">Provide the outcome which is results or the predictive model over data.<\/span><\/li>\n<\/ul>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">5. Visualization of Data<\/span><\/b><\/h4>\n<ul style=\"text-align: justify;\">\n<li><span lang=\"EN-GB\">The output result is visualized through the tool to provide a better understanding of the data.<\/span><\/li>\n<\/ul>\n<blockquote>\n<p style=\"text-align: justify;\"><em>Global Hadoop Market is growing at a rapid rate. According to the trend analysis report, <a href=\"https:\/\/www.whizlabs.com\/blog\/global-hadoop-market-analysis-trends\/\" target=\"_blank\" rel=\"noopener\">Global Hadoop Market is expected to reach $84.6 billion by 2021.<\/a>\u00a0<\/em><\/p>\n<\/blockquote>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Hadoop_and_Big_Data_Predictive_Analytics\"><\/span><b><span lang=\"EN-GB\">Hadoop and Big Data Predictive Analytics<\/span><\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Managing the data analytics life cycle of a predictive model has several advantages when analyzed through Hadoop.<\/span><\/p>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">Data Sourcing<\/span><\/b><\/h4>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Hadoop distributed file system (HDFS) works as the data source for predictive analysis in a distributed cluster data management system.<\/span><\/p>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">Open Source Analytics<\/span><\/b><\/h4>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Predictive modeling algorithms in an open source platform like<\/span><span lang=\"EN-GB\"> Hadoop ecosystem have its own pros. A statistical programming language like R works well with its open source analytic algorithms in Hadoop environment. Besides, Apache Spark and Mahout also have inbuilt predictive analysis algorithms, and they can also fast analyze large sets of data.<\/span><a href=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2024\/05\/hadoop-predictive-analytics.png\"><img decoding=\"async\" class=\"aligncenter wp-image-64515 size-full\" src=\"https:\/\/www.whizlabs.com\/blog\/wp-content\/uploads\/2024\/05\/hadoop-predictive-analytics.png\" alt=\"Big Data Predictive Analytics\" width=\"734\" height=\"269\" \/><\/a><\/p>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">Data Exploration<\/span><\/b><\/h4>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Hadoop, by default, is ideally suited for large sets of batch data processing. With the initiatives from HortonWorks and Cloudera, Hadoop data is now accessible through Hive and Impala in interactive mode.<\/span><\/p>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">Secure Analytics<\/span><\/b><\/h4>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Hadoop is an open-source platform. Hence security like authorization and authentication may be a concerning parameter for Hadoop. Predictive analytics involve different teams as discussed above.<\/span><\/p>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Hence, as a predictive analytics tool, it must cover up the gap. With the initiatives from Cloudera and Hortonworks, Hadoop has already achieved those solutions.<b><\/b><\/span><\/p>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">Better Workflow Management<\/span><\/b><\/h4>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Hadoop ecosystem comes with workflow management projects like <\/span><span lang=\"EN-GB\">Oozie<\/span><span lang=\"EN-GB\"> workflow scheduler. Though not specifically tailored to a predictive analytics life cycle, this tool works well for data scientists.<\/span><\/p>\n<blockquote>\n<p style=\"text-align: justify;\"><em>Hadoop is now not only for Data Scientists but for developers too. Here are the <a href=\"https:\/\/www.whizlabs.com\/blog\/why-java-developers-should-learn-hadoop\/\" target=\"_blank\" rel=\"noopener\">5 reasons why Java Developers should learn Hadoop.<\/a><\/em><\/p>\n<\/blockquote>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Hadoop_Challenges_for_Big_Data_Analytics\"><\/span><b><span lang=\"EN-GB\">Hadoop Challenges for Big Data Analytics<\/span><\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">As we have highlighted the important considerable factors for predictive analytics, the same applies to Hadoop in few core areas. These areas must be considered to make Hadoop a viable predictive analytics tool for data science.<\/span><\/p>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">Scaling Issue<\/span><\/b><\/h4>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">With the growing set of large data, Hadoop may not perform well during predictive analysis. So, when it is a question of choosing the right algorithms with massive data volumes scalability might be a concern.<\/span><\/p>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Similarly, the two tools in Hadoop ecosystem Apache Spark and Mahout have a limited set of predictive analytic algorithms. Hence, this is another area to improve to achieve the decent choice of algorithms.<\/span><\/p>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">Security Concerns<\/span><\/b><\/h4>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Though Hortonworks and Cloudera have helped to improve security performance of Hadoop, <\/span><span lang=\"EN-GB\">however, their core focus is on data management and not data modeling. Hence, data modeling part needs improvement considering the production data model.<\/span><\/p>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">Data Exploration with Visualization<\/span><\/b><\/h4>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Sometimes predictive analytics functionalities go beyond its life cycle which involves data exploration through interactive visualizations on the massive amount of data. <\/span><\/p>\n<h4 style=\"text-align: justify;\"><b><span lang=\"EN-GB\">Better Workflow<\/span><\/b><\/h4>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">This area needs more improvement in Hadoop. To organize different lifecycle stages of predictive analytics or to implement business rules, Hadoop workflow management needs enhancement with more functionality.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span><b><span lang=\"EN-GB\">Conclusion<\/span><\/b><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">While predictive analytics identifies meaningful patterns from big data, knowing Hadoop significantly helps for better analysis. Though knowing Hadoop is not mandatory for a data scientist, but a comprehensive Hadoop knowledge works as an added advantage. <\/span><\/p>\n<p style=\"text-align: justify;\"><span lang=\"EN-GB\">Whizlabs offers the Hadoop courses like <\/span><em><span lang=\"EN-GB\"><a href=\"https:\/\/www.whizlabs.com\/spark-developer-certification\/\" target=\"_blank\" rel=\"noopener\">Spark developer certification<\/a><\/span><\/em><span lang=\"EN-GB\"> guide and <\/span><span lang=\"EN-GB\">Hadoop<\/span> <span lang=\"EN-GB\">administration exam guide for <\/span><em><span lang=\"EN-GB\"><a href=\"https:\/\/www.whizlabs.com\/hdpca-certification\/\" target=\"_blank\" rel=\"noopener\">Hortonworks<\/a><\/span><\/em><span lang=\"EN-GB\"> and <\/span><span lang=\"EN-GB\"><em><a href=\"https:\/\/www.whizlabs.com\/cloudera-cca-admin-certification\/\" target=\"_blank\" rel=\"noopener\">Cloudera<\/a><\/em>. <\/span><span lang=\"EN-GB\">For a data scientist who wants to achieve a comprehensive knowledge of Hadoop ecosystem and insights, these courses will help a lot.<\/span><\/p>\n<p>Wish you the best in your Big Data Hadoop career!<\/p>\n<p>Have any query\/suggestion? Feel free to write us <strong><a href=\"http:\/\/ask.whizlabs.com\/c\/big-data\" target=\"_blank\" rel=\"noopener\">here<\/a><\/strong> or just put a comment below, we will be happy to answer!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Big Data Analytics has obtained a new height with Hadoop. This open source big data processing platform helps in capturing, storing, and processing the massive volumes of unstructured data. The real-time data has gained enormous credibility with its revolutionary contribution in business.\u00a0Hadoop predictive analytics is today&#8217;s real-time recommendation to reduce cost and market analysis for better performance. Want to get one level up in your Hadoop career? Here is the list of\u00a0Best Hadoop Certifications in 2018.\u00a0Choose one and get certified now! Hadoop predictive analytics is the advanced analytics method that provides better insights on the customer, potential risks, product portfolio [&hellip;]<\/p>\n","protected":false},"author":220,"featured_media":66242,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_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":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"default","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":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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