{"id":1919,"date":"2018-03-27T19:42:26","date_gmt":"2018-03-27T19:42:26","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/?post_type=chapter&#038;p=1919"},"modified":"2024-04-25T02:44:01","modified_gmt":"2024-04-25T02:44:01","slug":"data-warehousing-and-data-mining","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/chapter\/data-warehousing-and-data-mining\/","title":{"raw":"Data Warehousing and Data Mining","rendered":"Data Warehousing and Data Mining"},"content":{"raw":"<div class=\"textbox learning-objectives\">\r\n<h3>Learning Objectives<\/h3>\r\n<ul>\r\n \t<li>Differentiate between data warehousing and data mining<\/li>\r\n<\/ul>\r\n<\/div>\r\n<img class=\"alignright wp-image-2563 size-medium\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/2986\/2018\/03\/13191119\/Screen-Shot-2018-04-13-at-12.10.05-PM-e1532030426916-300x209.png\" alt=\"decorative image\" width=\"300\" height=\"209\" \/>\r\n\r\nAll of the RIS we have discussed so far have one major thing in common\u2014an underlying database to store their unique data. Through the process of mergers and acquisitions, most large retailers inherit duplicative systems that continue to exist independent of each other due to the large cost of consolidation. With data \u201ceverywhere,\u201d retailers turn to the latest IT techniques.\r\n\r\nData warehouses (DW) are created to bring related information from disparate databases to one large database so that it can be easily analyzed.\r\n\r\nIn computing, a\u00a0data warehouse\u00a0(DW or DWH) is a system used for reporting and\u00a0data analysis, and is considered a core component of business intelligence. DWs are central repositories of integrated\u00a0data\u00a0from one or more disparate sources.\r\n\r\nOnce the data has been migrated to the DW, data scientists can begin to provide retail management with meaningful information through the practice of data mining. Data mining\u00a0is the process of discovering patterns in large\u00a0data\u00a0sets and involves methods at the intersection of machine learning, statistics, and database systems.\r\n\r\nWith the mining of information in the data warehouse, management can gain valuable insights as to how best to run the business. This is usually accomplished through queries and reporting.\r\n\r\nQueries are business questions translated into code to bring results from the DW. What is our best-selling product line? What is the profit margin on our private brand versus the name brand products? Who are our best customers? How do our online sales affect our inventory position for our stores?\r\n\r\nBusiness reporting is simply scheduling the most common or requested queries at regular intervals and pushing the information out to the organizations information consumers on a regular basis.\r\n\r\nOne of the most notable data warehouse success stories comes from the healthcare industry in the 1990\u2019s. A large national health management company had more than nine regional centers, each operating semi-independently. Each regional center had its own management and business infrastructure, including information technology.\r\n\r\nThe company\u2019s top medical experts noticed that the care being delivered for its diabetes patients was inconsistent across the regions. Some regions claimed that certain treatments were more effective, but came at a higher cost to the business. But the real problem was that the clinical data needed to understand what was the most effective treatment was locked up in 10 different databases, many of which were using different database software.\r\n\r\nA data warehouse was constructed, pooling the data from all of the regional warehouses and providing access for the first time for national clinical research analysis. Out of hundreds of different treatment programs, three were found to be the most effective, and of those, two were found to be the least expensive. These data warehouse results were a win for the patients, doctors and the business.\r\n<div class=\"textbox tryit\">\r\n<h3>Practice questions<\/h3>\r\nhttps:\/\/assess.lumenlearning.com\/practice\/7926e5fa-ae27-45d4-9c28-ef6358effd6e\r\n<\/div>","rendered":"<div class=\"textbox learning-objectives\">\n<h3>Learning Objectives<\/h3>\n<ul>\n<li>Differentiate between data warehousing and data mining<\/li>\n<\/ul>\n<\/div>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignright wp-image-2563 size-medium\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/2986\/2018\/03\/13191119\/Screen-Shot-2018-04-13-at-12.10.05-PM-e1532030426916-300x209.png\" alt=\"decorative image\" width=\"300\" height=\"209\" \/><\/p>\n<p>All of the RIS we have discussed so far have one major thing in common\u2014an underlying database to store their unique data. Through the process of mergers and acquisitions, most large retailers inherit duplicative systems that continue to exist independent of each other due to the large cost of consolidation. With data \u201ceverywhere,\u201d retailers turn to the latest IT techniques.<\/p>\n<p>Data warehouses (DW) are created to bring related information from disparate databases to one large database so that it can be easily analyzed.<\/p>\n<p>In computing, a\u00a0data warehouse\u00a0(DW or DWH) is a system used for reporting and\u00a0data analysis, and is considered a core component of business intelligence. DWs are central repositories of integrated\u00a0data\u00a0from one or more disparate sources.<\/p>\n<p>Once the data has been migrated to the DW, data scientists can begin to provide retail management with meaningful information through the practice of data mining. Data mining\u00a0is the process of discovering patterns in large\u00a0data\u00a0sets and involves methods at the intersection of machine learning, statistics, and database systems.<\/p>\n<p>With the mining of information in the data warehouse, management can gain valuable insights as to how best to run the business. This is usually accomplished through queries and reporting.<\/p>\n<p>Queries are business questions translated into code to bring results from the DW. What is our best-selling product line? What is the profit margin on our private brand versus the name brand products? Who are our best customers? How do our online sales affect our inventory position for our stores?<\/p>\n<p>Business reporting is simply scheduling the most common or requested queries at regular intervals and pushing the information out to the organizations information consumers on a regular basis.<\/p>\n<p>One of the most notable data warehouse success stories comes from the healthcare industry in the 1990\u2019s. A large national health management company had more than nine regional centers, each operating semi-independently. Each regional center had its own management and business infrastructure, including information technology.<\/p>\n<p>The company\u2019s top medical experts noticed that the care being delivered for its diabetes patients was inconsistent across the regions. Some regions claimed that certain treatments were more effective, but came at a higher cost to the business. But the real problem was that the clinical data needed to understand what was the most effective treatment was locked up in 10 different databases, many of which were using different database software.<\/p>\n<p>A data warehouse was constructed, pooling the data from all of the regional warehouses and providing access for the first time for national clinical research analysis. Out of hundreds of different treatment programs, three were found to be the most effective, and of those, two were found to be the least expensive. These data warehouse results were a win for the patients, doctors and the business.<\/p>\n<div class=\"textbox tryit\">\n<h3>Practice questions<\/h3>\n<p>\t<iframe id=\"assessment_practice_7926e5fa-ae27-45d4-9c28-ef6358effd6e\" class=\"resizable\" src=\"https:\/\/assess.lumenlearning.com\/practice\/7926e5fa-ae27-45d4-9c28-ef6358effd6e?iframe_resize_id=assessment_practice_id_7926e5fa-ae27-45d4-9c28-ef6358effd6e\" frameborder=\"0\" style=\"border:none;width:100%;height:100%;min-height:300px;\"><br \/>\n\t<\/iframe>\n<\/div>\n\n\t\t\t <section class=\"citations-section\" role=\"contentinfo\">\n\t\t\t <h3>Candela Citations<\/h3>\n\t\t\t\t\t <div>\n\t\t\t\t\t\t <div id=\"citation-list-1919\">\n\t\t\t\t\t\t\t <div class=\"licensing\"><div class=\"license-attribution-dropdown-subheading\">CC licensed content, Original<\/div><ul class=\"citation-list\"><li>Data Warehousing and Data Mining. <strong>Authored by<\/strong>: Bob Danielson. <strong>Provided by<\/strong>: Lumen Learning. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY: Attribution<\/a><\/em><\/li><\/ul><div class=\"license-attribution-dropdown-subheading\">CC licensed content, Shared previously<\/div><ul class=\"citation-list\"><li>Data Mining. <strong>Authored by<\/strong>: Arbeck. <strong>Provided by<\/strong>: Wikimedia Commons. <strong>Located at<\/strong>: <a target=\"_blank\" href=\"https:\/\/commons.wikimedia.org\/wiki\/File:Data_Mining.svg\">https:\/\/commons.wikimedia.org\/wiki\/File:Data_Mining.svg<\/a>. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY: Attribution<\/a><\/em><\/li><\/ul><\/div>\n\t\t\t\t\t\t <\/div>\n\t\t\t\t\t <\/div>\n\t\t\t <\/section>","protected":false},"author":62559,"menu_order":5,"template":"","meta":{"_candela_citation":"[{\"type\":\"original\",\"description\":\"Data Warehousing and Data Mining\",\"author\":\"Bob Danielson\",\"organization\":\"Lumen Learning\",\"url\":\"\",\"project\":\"\",\"license\":\"cc-by\",\"license_terms\":\"\"},{\"type\":\"cc\",\"description\":\"Data Mining\",\"author\":\"Arbeck\",\"organization\":\"Wikimedia Commons\",\"url\":\"https:\/\/commons.wikimedia.org\/wiki\/File:Data_Mining.svg\",\"project\":\"\",\"license\":\"cc-by\",\"license_terms\":\"\"}]","CANDELA_OUTCOMES_GUID":"41d5132b-3f0a-4802-a4b2-d358006f7fb9, f08781c1-e85a-4c60-a956-cde1fbe5593e","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-1919","chapter","type-chapter","status-publish","hentry"],"part":1910,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/pressbooks\/v2\/chapters\/1919","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/wp\/v2\/users\/62559"}],"version-history":[{"count":18,"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/pressbooks\/v2\/chapters\/1919\/revisions"}],"predecessor-version":[{"id":6442,"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/pressbooks\/v2\/chapters\/1919\/revisions\/6442"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/pressbooks\/v2\/parts\/1910"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/pressbooks\/v2\/chapters\/1919\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/wp\/v2\/media?parent=1919"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/pressbooks\/v2\/chapter-type?post=1919"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/wp\/v2\/contributor?post=1919"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-retailmanagement\/wp-json\/wp\/v2\/license?post=1919"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}