{"id":8933,"date":"2020-07-16T06:43:50","date_gmt":"2020-07-16T06:43:50","guid":{"rendered":"https:\/\/www.experfy.com\/blog\/?p=8933"},"modified":"2023-11-28T13:51:34","modified_gmt":"2023-11-28T13:51:34","slug":"4-steps-in-prepping-your-enterprise-for-machine-learning","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/ai-ml\/4-steps-in-prepping-your-enterprise-for-machine-learning\/","title":{"rendered":"4 Steps In Prepping Your Enterprise For Machine Learning"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"8933\" class=\"elementor elementor-8933\" 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-785b3a8d elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"785b3a8d\" 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-4fe827b8\" data-id=\"4fe827b8\" 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-7c99b581 elementor-widget elementor-widget-text-editor\" data-id=\"7c99b581\" 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\n<p>While implementation of machine learning (ML) is still misunderstood, there\u2019s never been a better time to learn more about the technological tools and processes needed to facilitate the generation of data-derived insights. As such, ML is vital for enterprises, because it helps accommodate to the ever-growing number of data, thus paving the way for better insights. Once ML\u2019s true infrastructure is realized, companies can learn to better understand the data, and use it to produce more efficient and revenue-generating products.<\/p>\n\n\n\n<p>Today, we\u2019ll talk about the four steps that you can follow, so that implementing ML in your enterprise will be a breeze.<\/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-822331b elementor-widget elementor-widget-heading\" data-id=\"822331b\" 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\"><h2><strong>Step 1: Data Sourcing<\/strong><\/h2><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dd8661d elementor-widget elementor-widget-text-editor\" data-id=\"dd8661d\" 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\n<p>\u201cWhen you\u2019re sourcing data, you have to look at the various types of inputs to the algorithm,\u201d says Ethel Velez, a tech writer at <a href=\"https:\/\/nextcoursework.com\/\" rel=\"noopener\">Nextcoursework<\/a> and <a href=\"https:\/\/originwritings.com\/research-paper-help\" rel=\"noopener\">Originwritings<\/a>, \u201cas well as what technologies you\u2019ll need to look into these sources, and through what processes.\u201d<\/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-a49533f elementor-widget elementor-widget-heading\" data-id=\"a49533f\" 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<h4 class=\"elementor-heading-title elementor-size-default\"><h4>Here are some examples of data sources:<\/h4><\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ec35132 elementor-widget elementor-widget-text-editor\" data-id=\"ec35132\" 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\n<ul class=\"wp-block-list\">\n<li>Core transactions<\/li>\n<li>Information provided by customers<\/li>\n<li>External databases<\/li>\n<li>Market research data<\/li>\n<li>Social media<\/li>\n<li>Site traffic<\/li>\n<\/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-77c07d6 elementor-widget elementor-widget-heading\" data-id=\"77c07d6\" 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\"><h2><strong>Step 2: Create A Trusted Zone<\/strong><\/h2><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f0e86d5 elementor-widget elementor-widget-text-editor\" data-id=\"f0e86d5\" 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\n<p>Sourced data can then be curated through an SSOT, which structures it into a consistent place. With that said, validity and quality matter. Before data can be fed into ML, it has to be aggregated, reconciled, and validated.<\/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-653549c elementor-widget elementor-widget-heading\" data-id=\"653549c\" 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<h4 class=\"elementor-heading-title elementor-size-default\"><h4>Here are key attributes of a trusted zone:<\/h4>\n<!-- \/wp:heading --><\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-250b836 elementor-widget elementor-widget-text-editor\" data-id=\"250b836\" 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\n<!-- wp:list -->\n<ul>\n<li>A central repository of data (aggregated from multiple channels)<\/li>\n<li>Data elements (clearly defined and documented) and data lineage<\/li>\n<li>Documentation of assumptions (In other words, recent data prevails, if new data conflicts with old)<\/li>\n<li>Protocol for addressing unintended exceptions<\/li>\n<li>Daily reporting<\/li>\n<li>Vertical and Horizontal Architecture<\/li>\n<li>A data store that:\n<ul>\n<li>Houses the trusted zone<\/li>\n<\/ul>\n<ul>\n<li>Has high availability, AND<\/li>\n<\/ul>\n<ul>\n<li>Is resilient to failure.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<!-- \/wp:list -->\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-f18d016 elementor-widget elementor-widget-heading\" data-id=\"f18d016\" 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\">Now, data stores can be hosted on cloud platforms, which have benefits like:<\/h4>\n<!-- \/wp:heading --><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2f2991f elementor-widget elementor-widget-text-editor\" data-id=\"2f2991f\" 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<!-- wp:list -->\n<ul>\n<li>High availability<\/li>\n<li>Cost-effective, AND<\/li>\n<li>Horizontal and vertical scaling<\/li>\n<\/ul>\n<!-- \/wp:list -->\n\n<!-- wp:paragraph -->\n<p>Though, there are still concerns, in regards to privacy and security. Now more than ever, data is valuable, and can be breached at any day, any time \u2013 and ML is no exception to this.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>To ensure data compliance, your security and risk management teams must initiate and monitor best security practices, and even learn how to handle any possible breaches. Also, make sure that any cloud vendors that you do business with are held accountable, whenever something goes wrong. And, enable data encryption, before it\u2019s transmitted to the cloud, even when done over a secured virtual private network.<\/p>\n<!-- \/wp:paragraph -->\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-bba1acc elementor-widget elementor-widget-heading\" data-id=\"bba1acc\" 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\"><h2><strong>Step 3: Model Building For ML<\/strong><\/h2>\n<!-- \/wp:heading --><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-459b7da elementor-widget elementor-widget-text-editor\" data-id=\"459b7da\" 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<!-- wp:paragraph -->\n<p>\u201cMany companies are building ML-friendly models through software developing,\u201d says Lara Payne, a journalist at <a href=\"https:\/\/phdkingdom.com\/thesis-writing-service\" rel=\"noopener\">Phdkingdom<\/a> and <a href=\"https:\/\/1day2write.com\/\" rel=\"noopener\">1Day2write<\/a>. \u201cHowever, building a model on your own comes with setbacks, if not done properly. The problem is that when they use software development in place of actually building an ML model, then they\u2019re not getting the whole thing \u2013 it\u2019s like buying milk that is half-empty.\u201d<\/p>\n<!-- \/wp:paragraph -->\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-6cae412 elementor-widget elementor-widget-heading\" data-id=\"6cae412\" 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<h4 class=\"elementor-heading-title elementor-size-default\">\n<!-- wp:heading {\"level\":4} -->\n<h4>In that case, ML model building still needs the right tools, so that the ML\u2019s entire lifecycle is accounted for. The tools you would still need are:<\/h4>\n<!-- \/wp:heading --><\/h4>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-347e043 elementor-widget elementor-widget-text-editor\" data-id=\"347e043\" 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<!-- wp:list -->\n<ul>\n<li>Model deployment<\/li>\n<li>Monitoring<\/li>\n<li>Operations<\/li>\n<\/ul>\n<!-- \/wp:list -->\n\n<!-- wp:paragraph -->\n<p>Although model lifecycle management is still a work-in-progress itself, the data community is always updating the tools needed to make model development easier.<\/p>\n<!-- \/wp:paragraph -->\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-4a2d742 elementor-widget elementor-widget-heading\" data-id=\"4a2d742\" 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\"><h2><strong>Step 4: Get Insights<\/strong><\/h2>\n<!-- \/wp:heading --><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-979d59d elementor-widget elementor-widget-text-editor\" data-id=\"979d59d\" 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<!-- wp:paragraph -->\n<p>Real-time insights are important, because they show valuable data like customer behavior and potential fraudulent transactions. And, these insights need to be processed, generated, and delivered within short time frames or in near real-time. All you need to do is create a web service-based API layer dedicated to the compute tier. And, you\u2019ll need your real-time models registered to the API layer, which will enable applications to retrieve information on how to structure API requests and the expected structure of output.<\/p>\n<!-- \/wp:paragraph -->\n\n<!-- wp:paragraph -->\n<p>Though, ML models differ from traditional ones, because they are always learning. To help ML continue learning, you would have to create a training feedback loop and save inputs passed to the model, along with the resulting outputs (which need to be meaningful).<\/p>\n<!-- \/wp:paragraph -->\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-6518617 elementor-widget elementor-widget-heading\" data-id=\"6518617\" 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\"><!-- wp:heading -->\n<h2><strong>Conclusion<\/strong><\/h2><!-- \/wp:heading --><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7ac2871 elementor-widget elementor-widget-text-editor\" data-id=\"7ac2871\" 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<!-- wp:paragraph -->\n<p>As you read through these four steps, we hope that they helped you better understand machine learning, and how you can use it for your enterprise. As you can tell, ML has enormous potential, but it&#8217;s important to ensure that your organization can take advantage of it all. By hiring ML-specific experts, implementing success metrics, and efficient model-building, your organization will soon be ML-friendly.<\/p>\n<!-- \/wp:paragraph -->\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>Machine learning has enormous potential, but it&#8217;s important to ensure that your organization can take advantage of it all. Implementing success metrics, and efficient model-building, your organization will soon be ML-friendly. We\u2019ll talk about the four steps that you can follow, so that implementing ML in your enterprise will be a breeze.<\/p>\n","protected":false},"author":863,"featured_media":8934,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[183],"tags":[458,92,457],"ppma_author":[3956],"class_list":["post-8933","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-ml","tag-implementing","tag-machine-learning","tag-model-building"],"authors":[{"term_id":3956,"user_id":863,"is_guest":0,"slug":"vk","display_name":"Vanessa Kearney","avatar_url":"https:\/\/www.experfy.com\/blog\/wp-content\/uploads\/2020\/07\/Vanessa-Kearney.jpg","user_url":"https:\/\/academicbrits.com\/","last_name":"Kearney","first_name":"Vanessa","job_title":"","description":"Vanessa Kearney is a writer and editor at Academicbrits.com. As a professional writer, she writes about many topics, and she strives to create the best content in the writing industry."}],"_links":{"self":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/8933","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\/863"}],"replies":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/comments?post=8933"}],"version-history":[{"count":7,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/8933\/revisions"}],"predecessor-version":[{"id":34452,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/8933\/revisions\/34452"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media\/8934"}],"wp:attachment":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media?parent=8933"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/categories?post=8933"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/tags?post=8933"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/ppma_author?post=8933"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}