{"id":49203,"date":"2009-05-04T06:11:13","date_gmt":"2009-05-04T03:11:13","guid":{"rendered":"https:\/\/www.altoros.com\/blog\/?p=49203"},"modified":"2021-10-23T23:27:22","modified_gmt":"2021-10-23T20:27:22","slug":"sources-of-poor-data-quality","status":"publish","type":"post","link":"https:\/\/www.altoros.com\/blog\/sources-of-poor-data-quality\/","title":{"rendered":"The Reasons for Poor Data Quality"},"content":{"rendered":"<p><center><\/p>\n<p><small>(<a href=\"https:\/\/www.iqint.org\/publication2011\/pierce-2008-04.shtml\" 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\/sources-of-poor-data-quality\/#Data_quality_is_still_an_issue\" >Data quality is still an issue<\/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\/sources-of-poor-data-quality\/#Seven_sources_of_poor_data\" >Seven sources of poor data<\/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\/sources-of-poor-data-quality\/#Further_reading\" >Further reading<\/a><\/li><\/ul><\/nav><\/div>\n<h3><span class=\"ez-toc-section\" id=\"Data_quality_is_still_an_issue\"><\/span>Data quality is still an issue<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Lately, there have been <a href=\"https:\/\/www.altoros.com\/blog\/data-management-longs-for-data-quality-solid-grounds\/\">talks<\/a> about the need for intersection between data integration and <a href=\"https:\/\/www.altoros.com\/blog\/wrong-approach-to-data-quality-right-approach-to-data-quality\/\">data quality<\/a> functionality. True, no integration initiative can be called successful without the accuracy and relevance of the information provided. The benefits of this consolidation are quite obvious: a consistent and complete view of corporate data, and, as a result, the ability to improve business processes faster to conquer the markets.<\/p>\n<p>Some steps have already been made toward binding technology offerings and enhancing their features, however, <a href=\"https:\/\/www.altoros.com\/blog\/the-role-of-data-stewards-in-data-integration\/\">data management<\/a> still remains a challenge today. According to Gartner, three-quarters of F1000 companies <a href=\"https:\/\/www.computerweekly.com\/news\/2240081356\/More-than-a-quarter-of-business-data-inaccurate\" rel=\"noopener noreferrer\" target=\"_blank\">struggle<\/a> with data quality, having 25% of their critical data inaccurate, duplicated, or incomplete. Last year&#8217;s report from the International Association for Information and Data Quality <a href=\"https:\/\/www.iqint.org\/publication2011\/pierce-2008-04.shtml\" rel=\"noopener noreferrer\" target=\"_blank\">revealed<\/a> that data governance initiatives were still at their early stages.<\/p>\n<p>The reason lies in the difficulty of understanding what quality data is and in estimating the cost of <a href=\"https:\/\/www.altoros.com\/blog\/solving-data-quality-problems-in-three-steps\/\">bad data<\/a>. It isn\u2019t always clear why or how to correct this problem, because poor data quality presents itself in many different ways.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2009\/05\/Focus-of-information-data-governance-efforts.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2009\/05\/Focus-of-information-data-governance-efforts-1024x730.png\" width=\"720\" class=\"aligncenter size-large wp-image-64362\" \/><\/a><small>The focus of data governance efforts at an enterprise (<a href=\"https:\/\/www.iqint.org\/publication2011\/pierce-2008-04.shtml\" rel=\"noopener noreferrer\" target=\"_blank\">Image credit<\/a>)<\/small><\/center><\/p>\n<p>A better understanding of the underlying sources that generate quality issues can help develop a proactive and strategic plan to address the problem.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Seven_sources_of_poor_data\"><\/span>Seven sources of poor data<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Last month, I stumbled upon an <a href=\"https:\/\/web.archive.org\/web\/20090402143159\/http:\/\/www.information-management.com\/issues\/2007_57\/data_quality-10015139-1.html\" rel=\"noopener noreferrer\" target=\"_blank\">article<\/a> by <a href=\"https:\/\/www.linkedin.com\/in\/wmcknight\/\" rel=\"noopener noreferrer\" target=\"_blank\">William McKnight<\/a>, where he describes the seven possible sources of poor data quality. Here they are, in the order of their occurrence:<\/p>\n<div id=\"attachment_62218\" style=\"width: 160px\" class=\"wp-caption alignright\"><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2008\/09\/William-McKnight.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-62218\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2008\/09\/William-McKnight-150x150.jpg\" width=\"150\" height=\"150\" class=\"size-thumbnail wp-image-62218\" \/><\/a><p id=\"caption-attachment-62218\" class=\"wp-caption-text\"><small>William McKnight<\/small><\/p><\/div>\n<ul>\n<li style=\"margin-bottom:6px;\"><b>Entry quality<\/b>\u2014usually caused by a person entering data into a system. The problem may occur due to a typo or a intentional decision, such as providing a dummy phone number or address. Identifying these outliers or missing data is easily accomplished with profiling tools or simple queries.<\/li>\n<li style=\"margin-bottom:6px;\"><b>Process quality<\/b>\u2014such issues occur systematically as data <a href=\"https:\/\/www.altoros.com\/blog\/the-three-most-common-problems-faced-during-data-migration\/\">moves<\/a> through an organization. They may result from a system crash, file loss, or any other technical accident that results from integrated systems. These problems are often difficult to identify, especially if the data has made a number of <a href=\"https:\/\/www.altoros.com\/blog\/etl-whats-in-abbreviation\/\">transformations<\/a> on the way to its destination. Process quality can usually be remedied easily once the source of the problem is identified. Proper checks and quality control at each touch point along the path is needed to ensure that problems are rooted out, though these checks may often be absent in legacy processes.<\/li>\n<li style=\"margin-bottom:6px;\"><b>Identification quality<\/b>\u2014resulting from a failure to recognize the relationship between two objects. For example, two similar products with different <a href=\"https:\/\/en.wikipedia.org\/wiki\/Stock_keeping_unit\" rel=\"noopener noreferrer\" target=\"_blank\">SKUs<\/a> are incorrectly judged to be the same. Identification quality may have significant associated costs, such as mailing the same household more than once (learn how to address this <a href=\"https:\/\/www.altoros.com\/blog\/data-cleansing-and-validation-using-strikeiron-services-and-apatar\/\">here<\/a>). Data quality processes can largely eliminate this problem by matching records, identifying duplicates, and placing a confidence score on the similarity of records.<\/li>\n<\/ul>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2009\/05\/Overall-objectives-of-information-data-governance-efforts.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2009\/05\/Overall-objectives-of-information-data-governance-efforts-1024x736.png\" width=\"720\" class=\"aligncenter size-large wp-image-64364\" \/><\/a><small>The main goals of data governance (<a href=\"https:\/\/www.iqint.org\/publication2011\/pierce-2008-04.shtml\" rel=\"noopener noreferrer\" target=\"_blank\">Image credit<\/a>)<\/small><\/center><\/p>\n<ul>\n<li style=\"margin-bottom:6px;\"><b>Integration quality<\/b>\u2014occurring due to failed integration of all the known information about an object, which, normally, should be done to provide an accurate representation of the object.<\/li>\n<li style=\"margin-bottom:6px;\"><b>Usage quality<\/b>\u2014caused by incorrect use and interpretation of the information at the point of access.<\/li>\n<li style=\"margin-bottom:6px;\"><b>Aging quality<\/b>\u2014occurring as the information that can no longer be trusted due to the fact that time passes and the information become outdated.<\/li>\n<li><b>Organizational quality<\/b>\u2014which may occur when the information is reconciled between two systems based on the way the organization constructs and views the data.<\/li>\n<\/ul>\n<p>Today, data quality is no longer a domain of just a <a href=\"https:\/\/www.altoros.com\/blog\/5-things-to-watch-out-for-in-data-warehousing\/\">data warehouse<\/a> or ETL\u2014it is accepted as an enterprise-wide responsibility. Having necessary tools, experience, and <a href=\"https:\/\/www.altoros.com\/blog\/the-dos-and-donts-of-data-integration\/\">best practices<\/a>, companies can address the issues with &#8216;dirty&#8217; data before it reaches decision-makers.<\/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\/data-quality-upstream-or-downstream\/\">Data Quality: Upstream or Downstream?<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/solving-data-quality-problems-in-three-steps\/\">Solving the Problems Associated with \u201cDirty\u201d Data<\/a><\/li>\n<li><a href=\"https:\/\/www.altoros.com\/blog\/data-management-longs-for-data-quality-solid-grounds\/\">MDM Longs for Data Quality and Solid Grounds<\/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> with contributions from <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)<\/p>\n<p>&nbsp;<\/p>\n<p>Data quality is still an issue<\/p>\n<p>Lately, there have been talks about the need for intersection between data integration and data quality functionality. True, no integration initiative can be called successful without the accuracy and relevance of the information provided. The benefits of this consolidation are quite obvious: a [&#8230;]<\/p>\n","protected":false},"author":81,"featured_media":64360,"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-49203","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>The Reasons for Poor Data Quality | Altoros<\/title>\n<meta name=\"description\" content=\"Learn which areas of the information flow within an enterprise require the most attention.\" \/>\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\/sources-of-poor-data-quality\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Reasons for Poor Data Quality | Altoros\" \/>\n<meta property=\"og:description\" content=\"(Featured image credit) &nbsp; Data quality is still an issue Lately, there have been talks about the need for intersection between data integration and data quality functionality. 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In addition, she has experience working as an interpreter and communications specialist.\",\"url\":\"https:\/\/www.altoros.com\/blog\/author\/olga\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"The Reasons for Poor Data Quality | Altoros","description":"Learn which areas of the information flow within an enterprise require the most attention.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.altoros.com\/blog\/sources-of-poor-data-quality\/","og_locale":"en_US","og_type":"article","og_title":"The Reasons for Poor Data Quality | Altoros","og_description":"(Featured image credit) &nbsp; Data quality is still an issue Lately, there have been talks about the need for intersection between data integration and data quality functionality. 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