{"id":6821,"date":"2025-09-13T07:02:19","date_gmt":"2025-09-13T07:02:19","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/09\/13\/a-focused-approach-to-learning-sql\/"},"modified":"2025-09-13T07:02:19","modified_gmt":"2025-09-13T07:02:19","slug":"a-focused-approach-to-learning-sql","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/09\/13\/a-focused-approach-to-learning-sql\/","title":{"rendered":"A Focused Approach to Learning SQL"},"content":{"rendered":"<p>    A Focused Approach to Learning SQL<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<p>Data is everywhere, but how do you draw insights from it? Often, structured data is stored in relational databases, meaning collections of related tables of data. For instance, a company might store customer purchases in one table, customer demographics in another, and suppliers in a third table. These tables can then be joined together and [\u2026]<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/a-focused-approach-to-learning-sql\/\">A Focused Approach to Learning SQL<\/a> appeared first on <a href=\"https:\/\/towardsdatascience.com\/\">Towards Data Science<\/a>.<\/p>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Mark Pedigo<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/a-focused-approach-to-learning-sql\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A Focused Approach to Learning SQL Data is everywhere, but how do you draw insights from it? Often, structured data is stored in relational databases, meaning collections of related tables of data. For instance, a company might store customer purchases in one table, customer demographics in another, and suppliers in a third table. These tables [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,211,83,403,160,2380,404,3773,3774],"tags":[1339,84,3474],"class_list":["post-6821","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-data-analysis","category-data-science","category-database","category-programming","category-sponsored-content","category-sql","category-sql-database","category-sql-for-beginners","tag-approach","tag-data","tag-focused"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6821"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=6821"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6821\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=6821"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=6821"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=6821"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}