{"id":22744,"date":"2021-04-15T09:07:00","date_gmt":"2021-04-15T09:07:00","guid":{"rendered":"https:\/\/www.experfy.com\/blog\/role-of-data-matching-in-big-data-business-strategy\/"},"modified":"2023-08-26T07:07:25","modified_gmt":"2023-08-26T07:07:25","slug":"role-of-data-matching-in-big-data-business-strategy","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/bigdata-cloud\/role-of-data-matching-in-big-data-business-strategy\/","title":{"rendered":"The Role Of Data Matching In Big Data Business Strategy"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"22744\" class=\"elementor elementor-22744\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-0b26ea7 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0b26ea7\" data-element_type=\"section\" data-e-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-dec10c9\" data-id=\"dec10c9\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-de4b55c elementor-widget elementor-widget-text-editor\" data-id=\"de4b55c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<blockquote class=\"wp-block-quote\"><p>\u201cIt is both staggering and exciting to imagine how data and analytic capabilities will transform entire industries.\u201d <\/p><cite>&#8211; Ariel Dora Stern<\/cite><\/blockquote>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7871495 elementor-widget elementor-widget-text-editor\" data-id=\"7871495\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>As promising as big data analytics sound, there\u2019s still a huge gap between a company\u2019s expectations with their data, and the reality. In the article <a href=\"https:\/\/hbswk.hbs.edu\/item\/companies-love-big-data-but-lack-strategy-to-use-it-effectively\" target=\"_blank\" rel=\"noreferrer noopener\" class=\"broken_link\"><em>Companies love big data but lack the strategy to use it effectively<\/em><\/a>, Harvard Business School shared some insights that they teach to executives. And it said:<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8f17081 elementor-widget elementor-widget-text-editor\" data-id=\"8f17081\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<blockquote class=\"wp-block-quote\"><p><em>\u201cThe problem is that, in many cases, big data is not used well. Companies are better at collecting data \u2013 about their customers, about their products, about competitors \u2013 than analyzing that data and designing strategy around it.\u201d<\/em><\/p><\/blockquote>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6c932ed elementor-widget elementor-widget-text-editor\" data-id=\"6c932ed\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>This clearly highlights not only the need for big data, but learning how to devise <a href=\"https:\/\/www.experfy.com\/blog\/fintech\/blockchain-the-networked-ecosystem-is-the-business\/\" target=\"_blank\" rel=\"noreferrer noopener\">business strategies<\/a> that incorporate it.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dfed4f8 elementor-widget elementor-widget-heading\" data-id=\"dfed4f8\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Big data \u2013 leveraging advanced analytics<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-07c1659 elementor-widget elementor-widget-text-editor\" data-id=\"07c1659\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Big data is something that consumes a lot of space (volume), at unprecedented speeds (velocity), and exists in different formats (variety). Big data, in itself, is not something that adds value to your business processes or strategies. You have to \u201cuse it well\u201d to extract all the insights and benefits out of it.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-966155f elementor-widget elementor-widget-heading\" data-id=\"966155f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">If your big data is used well, then it can help you to:<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-274a64b elementor-widget elementor-widget-text-editor\" data-id=\"274a64b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul><li>Optimize operational and business process by leveraging insights gathered about products, customers, and markets,<\/li><li>Comply with governmental standards and reduce risks,<\/li><li>Design a better, personalized customer experience, and<\/li><li>Discover new revenue opportunities.<\/li><\/ul>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3e74b64 elementor-widget elementor-widget-text-editor\" data-id=\"3e74b64\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Let&#8217;s talk about how organizations can use big data to achieve business goals.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a2c33cb elementor-widget elementor-widget-heading\" data-id=\"a2c33cb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Devising effective business strategies that incorporate big data<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-39494b4 elementor-widget elementor-widget-text-editor\" data-id=\"39494b4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Bill Schmarzo (known as the <em>Dean of Big Data<\/em>) explains it best when he reverse-engineers the process of achieving business goals using big data. He gives a 5-step approach for how it is done. I\u2019ll give a brief overview of those steps here, and you can read about it in detail at <a href=\"https:\/\/infocus.delltechnologies.com\/wp-content\/uploads\/2017\/04\/USF_The_Economics_of_Data_and_Analytics-Final3.pdf\" target=\"_blank\" rel=\"noreferrer noopener\" class=\"broken_link\">this link<\/a>.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fa91051 elementor-widget elementor-widget-heading\" data-id=\"fa91051\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">1. Identify desired business outcomes<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f248eff elementor-widget elementor-widget-text-editor\" data-id=\"f248eff\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>You must first identify the desired business outcomes of your business. Try to think of initiatives that will transform your business, or take it one step closer to success. For example, increasing online store sales by 10% in the next 12 months.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5641c5f elementor-widget elementor-widget-heading\" data-id=\"5641c5f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">2. Identify supporting use cases<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-77ad2d2 elementor-widget elementor-widget-text-editor\" data-id=\"77ad2d2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>This step is about realizing which use cases will help you to achieve the business outcomes listed in the first step. For example, if increase online sales by 10% is the desired business outcome, then its supporting use cases would be: advertise promotions on high-traffic sites, run email marketing campaigns, increase online lead generation, etc.&nbsp;<\/p>\n<p>Once the supporting use cases for each business outcome are realized, you need to assess the financial impact of each use case, its potential value, and implementation risks.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-11b6cc2 elementor-widget elementor-widget-heading\" data-id=\"11b6cc2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">3. Prioritize use cases<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-099983a elementor-widget elementor-widget-text-editor\" data-id=\"099983a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>In this step, your organization is required to prioritize all use cases so that you can focus on one use case at a time. This can be done by plotting the use case\u2019s implementation feasibility against business value.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6c52b26 elementor-widget elementor-widget-heading\" data-id=\"6c52b26\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">4. Identify data sources for each use case<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f5b2b1b elementor-widget elementor-widget-text-editor\" data-id=\"f5b2b1b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The implementation of every use case needs to be done using data. For example, to improve customer cross-selling, you need data from social media, market baskets, site traffic information, etc. In this step, every use case is related to one or more data sources to realize which source is used for any use case implementation.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f9df683 elementor-widget elementor-widget-heading\" data-id=\"f9df683\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">5. Compute economic value for each use case<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e7f060a elementor-widget elementor-widget-text-editor\" data-id=\"e7f060a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Once you have realized the data sources that you need to successfully execute each use case, you are now ready to compute the financial value a data source holds. This is done by aggregating the financial impacts of all use case implementations this data source will be used for.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3f6dd53 elementor-widget elementor-widget-heading\" data-id=\"3f6dd53\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Is it that simple?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-924d570 elementor-widget elementor-widget-text-editor\" data-id=\"924d570\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>We just saw how each data source holds an economic, financial value, and how it is used to successfully execute any use case that will help you achieve desired business outcomes. Every organization has access to their data. So, it must be pretty simple, and everyone should be doing it, right? What\u2019s the catch? Its data quality.<\/p>\n<p>Your data sources hold this economic value given that they measure up to 6 critical dimensions of data quality: data accuracy, validity, consistency, uniqueness, completeness, and timeliness.<\/p>\n<p>There is one challenge that is more complex than the others. And it is having unique data records across all data sources.<\/p>\n<p>Many times, data from multiple sources is needed to fully execute a single use case. For this reason, data is first merged and integrated so that it is present at one place, and can be used for analysis.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-095954a elementor-widget elementor-widget-heading\" data-id=\"095954a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Let\u2019s look at an example<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-26917ae elementor-widget elementor-widget-text-editor\" data-id=\"26917ae\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Companies usually have a number of data records in their databases for the same individual\/entity. It occurs due to storing work and personal email addresses of the same person as separate contacts, or incomplete information causes you to create new contacts rather than updating the existing ones, or the information is stored in disparate systems such as website tracking application, email campaign tool, etc.<\/p>\n<p>Whatever the reason, this is the most common obstacle that reduces the accuracy of big data analysis results. For instance, if your data contains duplicate records relating to the same person, you may end up sending an email campaign twice to an individual. This does not only damage your brand\u2019s customer experience, but it also makes the use case results inaccurate. You could count the click rates from the same individual multiple times and overestimate the effectiveness of your email campaign.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-58d2d0b elementor-widget elementor-widget-heading\" data-id=\"58d2d0b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Introducing data matching<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e4f4c8b elementor-widget elementor-widget-text-editor\" data-id=\"e4f4c8b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>When disparate datasets are merged and purged together, the data values become duplicated and inconsistent. If you base your big data business strategy on inaccurate data records, it will yield biased results. On the other hand, if you perform <a href=\"https:\/\/dataladder.com\/data-matching-software\" target=\"_blank\" rel=\"noreferrer noopener\">data matching<\/a> techniques, you can easily utilize this data for the execution of any use case or business process.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-002e935 elementor-widget elementor-widget-heading\" data-id=\"002e935\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How does data matching work?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8b4d958 elementor-widget elementor-widget-text-editor\" data-id=\"8b4d958\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Data matching is pretty simple when datasets contain unique identifiers, such as social security number, national identity number, etc. In such cases, you can simply compare both records\u2019 identifier and classify it as a match or a non-match.<\/p>\n<p>Things get complex when there are no unique identifiers in datasets or they cannot be used due to confidentiality purposes. In such cases, multiple variables are assigned weights and then evaluated together to classify matches and nonmatches.<\/p>\n<p>Organizations employ various data matching techniques such as phonetic, numeric, fuzzy matching, or other proprietary algorithms. Once matched, you can then decide to merge records or purge them so that each record in your big data only relates to a single entity.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ba061a8 elementor-widget elementor-widget-heading\" data-id=\"ba061a8\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Conclusion \u2013 the role of data matching in big data business strategy<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-290ea63 elementor-widget elementor-widget-text-editor\" data-id=\"290ea63\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The role of data matching and data quality is imperative when it comes to designing business strategies while incorporating big data. As we mapped out the process of devising these strategies, we noticed how every data source holds a financial value and it has great impact on the business outcomes you\u2019re looking to achieve with the supporting use cases.<\/p>\n\t\t\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>The role of data matching and data quality is imperative when it comes to designing business strategies while incorporating big data.<\/p>\n","protected":false},"author":903,"featured_media":19155,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[187],"tags":[863,95,393,205],"ppma_author":[3773],"class_list":["post-22744","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-bigdata-cloud","tag-advanced-analytics","tag-big-data-amp-technology","tag-business-strategy","tag-data"],"authors":[{"term_id":3773,"user_id":903,"is_guest":0,"slug":"javeria-gauhar-khan","display_name":"Javeria Gauhar Khan","avatar_url":"https:\/\/www.experfy.com\/blog\/wp-content\/uploads\/2020\/09\/Javeria-Gauhar-Khan-150x150.png","user_url":"https:\/\/dataladder.com\/%20","last_name":"Gauhar Khan","first_name":"Javeria","job_title":"","description":"Javeria Gauhar Khan, Technical SEO at Data Ladder LLC,  is an experienced B2B\/SaaS writer specializing in writing for the data management industry. She is also a programmer in developing, testing and maintaining enterprise software applications."}],"_links":{"self":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/22744","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/users\/903"}],"replies":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/comments?post=22744"}],"version-history":[{"count":4,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/22744\/revisions"}],"predecessor-version":[{"id":31563,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/22744\/revisions\/31563"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media\/19155"}],"wp:attachment":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media?parent=22744"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/categories?post=22744"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/tags?post=22744"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/ppma_author?post=22744"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}