{"id":49602,"date":"2008-11-14T01:32:46","date_gmt":"2008-11-13T22:32:46","guid":{"rendered":"https:\/\/www.altoros.com\/blog\/?p=49602"},"modified":"2021-07-13T21:32:30","modified_gmt":"2021-07-13T18:32:30","slug":"solving-data-quality-problems-in-three-steps","status":"publish","type":"post","link":"https:\/\/www.altoros.com\/blog\/solving-data-quality-problems-in-three-steps\/","title":{"rendered":"Solving the Problems Associated with &#8220;Dirty&#8221; Data"},"content":{"rendered":"<p><center><small>(<a href=\"https:\/\/www.slideshare.net\/datavaluetalk\/robert-winter-enterprise-wide-information-logistics-data-quality-summit-2008-presentation\" rel=\"noopener noreferrer\" target=\"_blank\">Featured image credit<\/a>)<\/small><\/center><\/p>\n<p>&nbsp;<\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_79_2 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.altoros.com\/blog\/solving-data-quality-problems-in-three-steps\/#Dont_waste_on_data_quality\" >Don\u2019t waste on data quality<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.altoros.com\/blog\/solving-data-quality-problems-in-three-steps\/#Data_quality_strategy_for_business_partners\" >Data quality strategy for business partners<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.altoros.com\/blog\/solving-data-quality-problems-in-three-steps\/#Further_reading\" >Further reading<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.altoros.com\/blog\/solving-data-quality-problems-in-three-steps\/#Related_slides\" >Related slides<\/a><\/li><\/ul><\/nav><\/div>\n<h3><span class=\"ez-toc-section\" id=\"Dont_waste_on_data_quality\"><\/span>Don\u2019t waste on data quality<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><a href=\"https:\/\/web.archive.org\/web\/20091213132940\/http:\/\/www.dmnews.com\/study-poor-data-quality-costs-600b-yearly\/article\/76513\" rel=\"noopener noreferrer\" target=\"_blank\">Data quality problems<\/a> cost U.S. businesses more than $600 billion a year,  according to The Data Warehousing Institute (2002). How does that happen? How come companies are losing this much money and not even realizing there\u2019s a way to save up?<\/p>\n<p>The major problem usually lies in the source the data is received from and the way it is processed before it enters the database\/warehouse (if processed at all). Then, there\u2019s also the currency of data, its accuracy, completeness, relevance, and consistency.<\/p>\n<p>A recent <a href=\"https:\/\/www.mediapost.com\/publications\/article\/92520\/marketers-should-avoid-dirty-data.html\" rel=\"noopener noreferrer\" target=\"_blank\">article<\/a> by <a href=\"https:\/\/www.linkedin.com\/in\/christopherpetix\/\" rel=\"noopener noreferrer\" target=\"_blank\">Christopher Petix<\/a> titled &#8220;Marketers Should Avoid <i>Dirty Data<\/i>&#8221; discusses the major benefits of generating your own CRM data as opposed to buying outdated information from data providers. Here are a few efforts and rules that can really make this approach stand out:<\/p>\n<ul>\n<li>collecting new data for every campaign<\/li>\n<li>ability to set parameters for data collection<\/li>\n<li>enabling consumers to fill out information related to their demographics <i>and<\/i> specify their interest in a specific product or service<\/li>\n<li>strict data cleansing processes, double-filtering, etc.<\/li>\n<\/ul>\n<div id=\"attachment_62490\" style=\"width: 140px\" class=\"wp-caption alignright\"><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2008\/11\/Christopher-Petix.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-62490\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2008\/11\/Christopher-Petix-150x150.jpg\" alt=\"\" width=\"130\" height=\"130\" class=\"size-thumbnail wp-image-62490\" \/><\/a><p id=\"caption-attachment-62490\" class=\"wp-caption-text\"><small>Christopher Petix<\/small><\/p><\/div>\n<p>All of the above ensure a hugher degree of relevance, and, as a result, really help you to save the money you\u2019d waste otherwise on reaching out irrelevant leads.<\/p>\n<blockquote><p>&#8220;So-called &#8216;dirty data&#8217; not only wastes contact center agents\u2019 time, it also wastes a marketer\u2019s budget\u2014and optimizing budgets is crucial in the current market conditions.&#8221; \u2014Christopher Petix<\/p><\/blockquote>\n<p>That\u2019s where  you realize that data quality could be taken care of in advance, but you\u2019re stuck with your dirty data and need to deal with it (and consequently spend more).<\/p>\n<blockquote><p>&#8220;Data quality has the ability to save marketers a considerable amount of money and is a completely transparent process.&#8221; \u2014Christopher Petix<\/p><\/blockquote>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Data_quality_strategy_for_business_partners\"><\/span>Data quality strategy for business partners<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Still, very often, data is received from third parties, including business partners such as suppliers or contractors. In this case, it&#8217;s worth talking to them about data quality.<\/p>\n<p><a href=\"https:\/\/www.linkedin.com\/in\/vicki-raeburn-5512693\/\" rel=\"noopener noreferrer\" target=\"_blank\">Vicki P. Raeburn<\/a> wrote <a href=\"https:\/\/web.archive.org\/web\/20080905035312\/http:\/\/www.dmreview.com\/issues\/2007_48\/10001362-1.html\" rel=\"noopener noreferrer\" target=\"_blank\">an article<\/a> for DM Review titled &#8220;Talking with Your Business Partners About Data Quality,&#8221; in which she discusses what needs to be done to solve bad data problems.<\/p>\n<div id=\"attachment_62308\" style=\"width: 140px\" class=\"wp-caption alignright\"><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2008\/06\/Vicki-Raeburn.png\"><img decoding=\"async\" aria-describedby=\"caption-attachment-62308\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2008\/06\/Vicki-Raeburn.png\" width=\"130\" class=\"size-thumbnail wp-image-62308\" \/><\/a><p id=\"caption-attachment-62308\" class=\"wp-caption-text\"><small>Vicki P. Raeburn<\/small><\/p><\/div>\n<blockquote><p>Solving the bad data problem requires:<\/p>\n<ul>\n<li>Clearly defining the nature of the problems your business partners\/customers are experiencing,<\/li>\n<li>Establishing priorities to tackle the most strategically important issues first, and<\/li>\n<li>Implementing an improvement plan with appropriate metrics and communications to your business partners\/customers.<\/li>\n<\/ul>\n<\/blockquote>\n<p>Vicki also names four dimensions for all business users to understand (which is also a problem, as most don\u2019t even know the problem <i>can<\/i> be dealt with) and keep in mind whenever working with the corporate data:<\/p>\n<blockquote>\n<ul>\n<li><strong>Timeliness<\/strong>: Currency of data elements.<\/li>\n<li><strong>Accuracy<\/strong>: Attributes of the entity (object) are correctly represented.<\/li>\n<li><strong>Completeness<\/strong>: Breadth (number of entities) and depth (number of fields defined and populated).<\/li>\n<li><strong>Consistency<\/strong>: Identity, definitions, hierarchies, standards and metrics are the same within and across databases.<\/li>\n<\/ul>\n<\/blockquote>\n<p>By implementing these initiatives, an organizaton can reduce the impact that &#8220;dirty&#8221; data can have on business operations.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Further_reading\"><\/span>Further reading<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/neglecting-the-quality-of-data-leads-to-failed-crm-projects\/\">Neglecting the Quality of Data Leads to Failed CRM Projects<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/data-quality-upstream-or-downstream\/\">Data Quality: Upstream or Downstream?<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/wrong-approach-to-data-quality-right-approach-to-data-quality\/\">Poor Data Quality Can Have Long-Term Effects<\/a><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Related_slides\"><\/span>Related slides<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><center><iframe loading=\"lazy\" src=\"\/\/www.slideshare.net\/slideshow\/embed_code\/key\/3ZWqyKsMWpDv2e\" width=\"595\" height=\"485\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" style=\"border:1px solid #CCC; border-width:1px; margin-bottom:5px; max-width: 100%;\" allowfullscreen> <\/iframe><\/center><\/p>\n<p>&nbsp;<\/p>\n<hr\/>\n<p><center><small>The post is written by <a href=\"https:\/\/www.altoros.com\/blog\/author\/alena-semeshko\/\">Alena Semeshko<\/a>, edited by <a href=\"https:\/\/www.altoros.com\/blog\/author\/alex\/\">Alex Khizhniak<\/a>.<\/small><\/center><\/p>\n","protected":false},"excerpt":{"rendered":"<p>(Featured image credit)<\/p>\n<p>&nbsp;<\/p>\n<p>Don\u2019t waste on data quality<\/p>\n<p>Data quality problems cost U.S. businesses more than $600 billion a year,  according to The Data Warehousing Institute (2002). How does that happen? How come companies are losing this much money and not even realizing there\u2019s a way to save up?<\/p>\n<p>The major problem [&#8230;]<\/p>\n","protected":false},"author":178,"featured_media":62487,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[7],"tags":[960,895],"class_list":["post-49602","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-and-opinion","tag-data-integration","tag-research-and-development"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Solving the Problems Associated with &quot;Dirty&quot; Data | Altoros<\/title>\n<meta name=\"description\" content=\"Pay attention to where you get your customer information from, as well as what you do during the data acquisition process.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.altoros.com\/blog\/solving-data-quality-problems-in-three-steps\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Solving the Problems Associated with &quot;Dirty&quot; Data | Altoros\" \/>\n<meta property=\"og:description\" content=\"(Featured image credit) &nbsp; Don\u2019t waste on data quality Data quality problems cost U.S. businesses more than $600 billion a year, according to The Data Warehousing Institute (2002). 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