{"id":3161,"date":"2019-12-23T16:46:15","date_gmt":"2019-12-23T16:46:15","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs\/?post_type=chapter&#038;p=3161"},"modified":"2024-05-17T01:53:05","modified_gmt":"2024-05-17T01:53:05","slug":"transforming-data","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/chapter\/transforming-data\/","title":{"raw":"Transforming Data","rendered":"Transforming Data"},"content":{"raw":"<div class=\"textbox learning-objectives\">\r\n<h3>Learning Outcomes<\/h3>\r\n<ul>\r\n \t<li>Transform data<\/li>\r\n<\/ul>\r\n<\/div>\r\nTransforming data is the process by which data is prepared for use in a database. One of the banes of a database administrator\u2019s existence is the need to \u201cclean\u201d data. Often, new data is available to be imported into a database but it is flawed in ways that make it unusable. One example would be a dataset that includes duplicate data. Other examples of data that requires cleaning or transformation are datasets with blank fields and concatenated strings.\r\n\r\nAccess provides some automated means of handling data transformation for duplicate records. If a dataset is suspected of containing duplicates, select the \u201cCreate\u201d command from the toolbar and click \u201cQuery Wizard\u201d and select \u201cFind Duplicates Query Wizard,\u201d identify the dataset in question and follow the instructions. A datasheet view will be created that shows records that appear to be duplicates.\r\n\r\n<img class=\"alignnone wp-image-3512 size-full\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/3008\/2019\/12\/07234640\/Figure14_22.png\" alt=\"New Query Dialog box. Find Duplicates Query Wizard is selected.\" width=\"595\" height=\"456\" \/>\r\n<div class=\"textbox tryit\">\r\n<h3>PRactice Question<\/h3>\r\nhttps:\/\/assess.lumenlearning.com\/practice\/7c9715e0-6865-4c18-8bf4-1c7cb7f3daef\r\n\r\n<\/div>\r\nDealing with impurities in datasets is a job not just for one application like MS Access. IT professionals in all disciplines are confronted with the need for some sort of data \u201cscrubbing\u201d or another, and it is safe to say that there are no bullet-proof, automated means of doing so. Using Access queries, views, and its programming language, does provide a means of identifying and correcting faulty datasets.","rendered":"<div class=\"textbox learning-objectives\">\n<h3>Learning Outcomes<\/h3>\n<ul>\n<li>Transform data<\/li>\n<\/ul>\n<\/div>\n<p>Transforming data is the process by which data is prepared for use in a database. One of the banes of a database administrator\u2019s existence is the need to \u201cclean\u201d data. Often, new data is available to be imported into a database but it is flawed in ways that make it unusable. One example would be a dataset that includes duplicate data. Other examples of data that requires cleaning or transformation are datasets with blank fields and concatenated strings.<\/p>\n<p>Access provides some automated means of handling data transformation for duplicate records. If a dataset is suspected of containing duplicates, select the \u201cCreate\u201d command from the toolbar and click \u201cQuery Wizard\u201d and select \u201cFind Duplicates Query Wizard,\u201d identify the dataset in question and follow the instructions. A datasheet view will be created that shows records that appear to be duplicates.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-3512 size-full\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/3008\/2019\/12\/07234640\/Figure14_22.png\" alt=\"New Query Dialog box. Find Duplicates Query Wizard is selected.\" width=\"595\" height=\"456\" \/><\/p>\n<div class=\"textbox tryit\">\n<h3>PRactice Question<\/h3>\n<p>\t<iframe id=\"assessment_practice_7c9715e0-6865-4c18-8bf4-1c7cb7f3daef\" class=\"resizable\" src=\"https:\/\/assess.lumenlearning.com\/practice\/7c9715e0-6865-4c18-8bf4-1c7cb7f3daef?iframe_resize_id=assessment_practice_id_7c9715e0-6865-4c18-8bf4-1c7cb7f3daef\" frameborder=\"0\" style=\"border:none;width:100%;height:100%;min-height:300px;\"><br \/>\n\t<\/iframe><\/p>\n<\/div>\n<p>Dealing with impurities in datasets is a job not just for one application like MS Access. IT professionals in all disciplines are confronted with the need for some sort of data \u201cscrubbing\u201d or another, and it is safe to say that there are no bullet-proof, automated means of doing so. Using Access queries, views, and its programming language, does provide a means of identifying and correcting faulty datasets.<\/p>\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-3161\">\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>Transforming Data. <strong>Authored by<\/strong>: Robert 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>\n\t\t\t\t\t\t <\/div>\n\t\t\t\t\t <\/div>\n\t\t\t <\/section>","protected":false},"author":17,"menu_order":15,"template":"","meta":{"_candela_citation":"[{\"type\":\"original\",\"description\":\"Transforming Data\",\"author\":\"Robert Danielson\",\"organization\":\"Lumen Learning\",\"url\":\"\",\"project\":\"\",\"license\":\"cc-by\",\"license_terms\":\"\"}]","CANDELA_OUTCOMES_GUID":"f92d00e2-b587-46e4-bff2-3cc40f9de00d, 0ba96ee9-b4f5-4df2-bbf4-6bf4b7f2b8da","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-3161","chapter","type-chapter","status-publish","hentry"],"part":2775,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/pressbooks\/v2\/chapters\/3161","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/wp\/v2\/users\/17"}],"version-history":[{"count":9,"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/pressbooks\/v2\/chapters\/3161\/revisions"}],"predecessor-version":[{"id":5987,"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/pressbooks\/v2\/chapters\/3161\/revisions\/5987"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/pressbooks\/v2\/parts\/2775"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/pressbooks\/v2\/chapters\/3161\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/wp\/v2\/media?parent=3161"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/pressbooks\/v2\/chapter-type?post=3161"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/wp\/v2\/contributor?post=3161"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-computerapplicationsmgrs-2\/wp-json\/wp\/v2\/license?post=3161"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}