{"id":49252,"date":"2009-03-23T07:22:30","date_gmt":"2009-03-23T04:22:30","guid":{"rendered":"https:\/\/www.altoros.com\/blog\/?p=49252"},"modified":"2021-10-27T05:00:55","modified_gmt":"2021-10-27T02:00:55","slug":"avoiding-common-data-quality-management-mistakes","status":"publish","type":"post","link":"https:\/\/www.altoros.com\/blog\/avoiding-common-data-quality-management-mistakes\/","title":{"rendered":"Avoiding Common Data Quality Management Mistakes"},"content":{"rendered":"<p><center><\/p>\n<p><small>(Featured image credit: <a href=\"http:\/\/download.101com.com\/pub\/tdwi\/files\/tdwi_bpr_dg_q208.pdf\" rel=\"noopener noreferrer\" target=\"_blank\">TDWI<\/a>)<\/small><\/p>\n<p><\/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\/avoiding-common-data-quality-management-mistakes\/#Major_issues\" >Major issues<\/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\/avoiding-common-data-quality-management-mistakes\/#What_to_do\" >What to do<\/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\/avoiding-common-data-quality-management-mistakes\/#Further_reading\" >Further reading<\/a><\/li><\/ul><\/nav><\/div>\n<h3><span class=\"ez-toc-section\" id=\"Major_issues\"><\/span>Major issues<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Due to the size and complexity of an organization, data quality management can be quite complicated and, sometimes, may turn (and very often it does) into a nightmare. There are three most common mistakes that companies make when starting a data quality management project:<\/p>\n<ol>\n<li style=\"margin-bottom:6px;\"><strong>Hoping for a \u201cmagic tool.\u201d<\/strong> It means that too often organizations believe a packaged solution can \u201cfix\u201d noncompliant data though in the first place they should care about eliminating the introduction of <a href=\"https:\/\/www.altoros.com\/blog\/solving-data-quality-problems-in-three-steps\/\">bad data<\/a>. Although data quality tools are the critical components of a data quality program, one must first question the motivation for purchasing a tool, then the process itself, and consider the improvement potential in terms of contributing to the effectiveness of the program.<\/li>\n<li style=\"margin-bottom:6px;\"><strong>Lack of the right expertise.<\/strong> The success in developing a <a href=\"https:\/\/www.altoros.com\/blog\/wrong-approach-to-data-quality-right-approach-to-data-quality\/\">data quality<\/a> management program depends on having both business and technical expertise but, in fact, lots of organizations disregard this crucial moment, being sure that as soon as a data quality program is initiated within an organization, there should be some visible improvement to the data. This is definitely wrong. Moreover, the data quality manager is often viewed as having responsibility for some data quality improvement action without necessarily having either the knowledge or authority to make it happen, and the team has no idea where to begin. This is the result of not bringing in the proper expertise to help get the program off the ground.<\/li>\n<li><strong>Not accounting for organizational culture changes.<\/strong> No technology in the world will eliminate data quality problems without understanding how people\u2019s behavior allows the introduction of information flaws in the first place. Without the cooperation of upstream systems owners, <a href=\"https:\/\/www.altoros.com\/blog\/5-things-to-watch-out-for-in-data-warehousing\/\">data warehousing<\/a> managers are often helpless to control the quality of incoming data. Stricter data quality needs at the data warehouse demand resource allocation by upstream managers.<\/li>\n<\/ol>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2009\/03\/tdwi-data-quality-survey-may-2006-russom.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2009\/03\/tdwi-data-quality-survey-may-2006-russom-1024x676.png\" width=\"720\" class=\"aligncenter size-large wp-image-64515\" \/><\/a><small>The scope of data qiality initiatives in 2006 (<a href=\"http:\/\/download.101com.com\/tdwi\/ww21\/0506wwd_E-mag.pdf\" rel=\"noopener noreferrer\" target=\"_blank\">image credit<\/a>)<\/small><\/center><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"What_to_do\"><\/span>What to do<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Here are some of the <a href=\"https:\/\/tdwi.org\/~\/media\/TDWI\/TDWI\/Research\/10M\/2005\/TenMistakes_Q3_05.ashx\" rel=\"noopener noreferrer\" target=\"_blank\">solutions<\/a> on how to avoid data quality management mistakes, as provided by <a href=\"https:\/\/www.linkedin.com\/in\/david-loshin-4a961\/\" rel=\"noopener noreferrer\" target=\"_blank\">David Loshin<\/a>, an expert in information management:<\/p>\n<div id=\"attachment_62606\" style=\"width: 160px\" class=\"wp-caption alignright\"><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2009\/03\/loshin-david.jpg\"><img decoding=\"async\" aria-describedby=\"caption-attachment-62606\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2009\/03\/loshin-david.jpg\" width=\"150\" class=\"size-thumbnail wp-image-62606\" \/><\/a><p id=\"caption-attachment-62606\" class=\"wp-caption-text\"><small>David Loshin<\/small><\/p><\/div>\n<blockquote>\n<ul>\n<li style=\"margin-bottom:6px;\">Exploit the advisory role of data quality teams and use internal procedures to attach responsibility and accountability for data quality improvement to the existing information management authority.<\/li>\n<li style=\"margin-bottom:6px;\">Don\u2019t forget training in the use of policies and procedures\u2014especially in the use of acquired tools.<\/li>\n<li style=\"margin-bottom:6px;\">Hire professionals with experience in managing data quality projects and programs from the start. These individuals will be able to identify opportunities for tactical successes that together contribute to the strategic success of the program.<\/li>\n<li>Engage external experts to help jump-start the improvement process. This will reassure your team that your problems are not unique and will allow you to learn from others\u2019 best practices.<\/li>\n<\/ul>\n<\/blockquote>\n<p>With proper <a href=\"https:\/\/www.altoros.com\/blog\/the-role-of-data-stewards-in-data-integration\/\">data governance<\/a> programs, <a href=\"https:\/\/www.altoros.com\/blog\/data-management-longs-for-data-quality-solid-grounds\/\">MDM<\/a>, and these recommendations, the quality of your data may eventually fit your business requirements.<\/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\/wrong-approach-to-data-quality-right-approach-to-data-quality\/\">Poor Data Quality Can Have Long-Term Effects<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/gartner-says-companies-lose-millions-due-to-poor-data-quality\/\">Gartner: Companies Lose Millions Due to Poor Data Quality<\/a><\/li>\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<\/ul>\n<hr\/>\n<p><center><small>The post is written by <a href=\"https:\/\/www.altoros.com\/blog\/author\/olga\/\">Olga Belokurskaya<\/a>; edited by <a href=\"https:\/\/www.altoros.com\/blog\/author\/alex\/\">Alex Khizhniak<\/a>.<\/small><\/center><\/p>\n","protected":false},"excerpt":{"rendered":"<\/p>\n<p>(Featured image credit: TDWI)<\/p>\n<\/p>\n<p>&nbsp;<\/p>\n<p>Major issues<\/p>\n<p>Due to the size and complexity of an organization, data quality management can be quite complicated and, sometimes, may turn (and very often it does) into a nightmare. There are three most common mistakes that companies make when starting a data quality management project:<\/p>\n<p>Hoping for a [&#8230;]<\/p>\n","protected":false},"author":81,"featured_media":63370,"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-49252","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>Avoiding Common Data Quality Management Mistakes | Altoros<\/title>\n<meta name=\"description\" content=\"Implementing a data quality management program is an important step for any organization.\" \/>\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\/avoiding-common-data-quality-management-mistakes\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Avoiding Common Data Quality Management Mistakes | Altoros\" \/>\n<meta property=\"og:description\" content=\"(Featured image credit: TDWI) &nbsp; Major issues Due to the size and complexity of an organization, data quality management can be quite complicated and, sometimes, may turn (and very often it does) into a nightmare. 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