{"id":48615,"date":"2010-12-07T06:56:29","date_gmt":"2010-12-07T03:56:29","guid":{"rendered":"https:\/\/www.altoros.com\/blog\/?p=48615"},"modified":"2021-10-26T05:31:06","modified_gmt":"2021-10-26T02:31:06","slug":"business-rules-for-data-quality","status":"publish","type":"post","link":"https:\/\/www.altoros.com\/blog\/business-rules-for-data-quality\/","title":{"rendered":"Implementing a Business Rules\u2013Based Approach to Data Quality"},"content":{"rendered":"<p><center><small>(<a href=\"https:\/\/www.slideshare.net\/holisticthinker\/alan-white-dg-combined2010\" 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\/business-rules-for-data-quality\/#Quality_metrics_and_thresholds\" >Quality metrics and thresholds<\/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\/business-rules-for-data-quality\/#Business_rules\" >Business rules<\/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\/business-rules-for-data-quality\/#Challenging_data_formats\" >Challenging data formats<\/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\/business-rules-for-data-quality\/#Related_slides\" >Related slides<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.altoros.com\/blog\/business-rules-for-data-quality\/#Further_reading\" >Further reading<\/a><\/li><\/ul><\/nav><\/div>\n<h3><span class=\"ez-toc-section\" id=\"Quality_metrics_and_thresholds\"><\/span>Quality metrics and thresholds<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Data integration experts consider information quality the main attribute for business users. Not only does the user need information to be delivered on time, but he or she also wants this information to be of a certain quality. Thus, <a href=\"https:\/\/www.altoros.com\/blog\/sources-of-poor-data-quality\/\">data quality<\/a> criteria are required to make this happen.<\/p>\n<p>At the early stages of an <a href=\"https:\/\/www.altoros.com\/blog\/the-dos-and-donts-of-data-integration\/\">information management<\/a> initiative, technical data quality criteria, such as <a href=\"https:\/\/searchdatamanagement.techtarget.com\/news\/2240022264\/Using-data-quality-metrics-to-build-a-data-quality-business-case\" rel=\"noopener noreferrer\" target=\"_blank\">metrics and thresholds<\/a>, are usually defined. These data quality parameters are business-independent, and contemporary data integration technologies can automatically evaluate them. These criteria may include:<\/p>\n<ul>\n<li style=\"margin-bottom:6px;\">Data types<\/li>\n<li style=\"margin-bottom:6px;\">Data domain compliance (domains refer to a set of allowable values\u2014for structured data, this can be a list of values, such as postal codes, a range of values between 1 and 100, etc.)<\/li>\n<li style=\"margin-bottom:6px;\">Statistical features of a data set (maximum value, minimum value, population distributions)<\/li>\n<li>Referential relationships<\/li>\n<\/ul>\n<p>However, is it enough to ensure <a href=\"https:\/\/en.wikipedia.org\/wiki\/Data_governance\" rel=\"noopener noreferrer\" target=\"_blank\">data governance<\/a>? Certainly, not.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2010\/12\/drivers-for-data-governance-efforts-2008.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2010\/12\/drivers-for-data-governance-efforts-2008-1024x712.png\" width=\"720\" class=\"aligncenter size-large wp-image-64468\" \/><\/a><small>The main drivers for data governance efforts (<a href=\"https:\/\/www.iqint.org\/publication2011\/pierce-2008-04.shtml\" rel=\"noopener noreferrer\" target=\"_blank\">Image credit<\/a>)<\/small><\/center><\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Business_rules\"><\/span>Business rules<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>To make the most out of an information management initiative for a coporate end user, other measures of data quality should involve <a href=\"https:\/\/en.wikipedia.org\/wiki\/Business_rules_approach\" rel=\"noopener noreferrer\" target=\"_blank\">business rules<\/a> compliance. For example, a mobile operator may establish as a business rule the number of months an account has a positive credit balance. All accounts with more than two months of negative balance are considered invalid. These criteria cannot be automatically evaluated solely by a data integration system\u2014business rules should be programmed.<\/p>\n<p>This approach can help to automate the decisions the company makes in its day-to-day operations. This also can be used to audit data for compliance with both external and internal regulations and policies. (Read the best practices for incorporating business rules into data governance \/ stewardship efforts in <a href=\"http:\/\/www.eiminstitute.org\/library\/eimi-archives\/volumn-4-issue-3-august-2010\/201crules-201d-2013-the-role-of-data-governance-in-business-rules\" rel=\"noopener noreferrer\" target=\"_blank\">this article<\/a> from The Enterprise Information Management Institute.)<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2010\/12\/tdwi-survey-2006-data-quality-supporting-business-initiatives.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2010\/12\/tdwi-survey-2006-data-quality-supporting-business-initiatives-1024x562.png\" width=\"720\" class=\"aligncenter size-large wp-image-64466\" \/><\/a><small>Business initiatives supported by data quality projects (<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>So, before acquiring a data quality solution, an organization should establish a set of business rules that later have to be transformed into code. Still, there is a number of chalenges, such as flexibility and limitations of this transformation, as well as other low-level issues known with data integration\u2014e.g., processing data formats when aggregating \/ consolidating several sources of information.<\/p>\n<p>&nbsp;<\/p>\n<h3><span class=\"ez-toc-section\" id=\"Challenging_data_formats\"><\/span>Challenging data formats<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><a href=\"https:\/\/www.altoros.com\/blog\/etl-whats-in-abbreviation\/\">ETL<\/a> tools should be able to find a standard way of handling a large variety of source and target data formats. This functionality is needed to implement comprehensive business rules within your data integration solution. Here&#8217;s how you can optimize an ETL tool to avoid issues with multiple data formats:<\/p>\n<ul>\n<li style=\"margin-bottom:6px;\">Make data normalization rules descriptive, don\u2019t hide them in procedural code blocks. Enable business people to specify rules in terms that make sense to them.<\/li>\n<li style=\"margin-bottom:6px;\">Set clear identification and reporting rules to detect the impact of data format changes, as well as maintenance rules, when a change occurs.<\/li>\n<li style=\"margin-bottom:6px;\">Rules should be expressed in terms of context-independent concepts that can easily be referred to by business people.<\/li>\n<li>Do not express business rules in physical field names, as it will require normalization functions to be created for each new source data format.<\/li>\n<\/ul>\n<p>Some ETL tools force developers into a variety of steps and complex procedures for accommodating the variation in source and target data formats. They lack the features to clearly express business rules (or comply with them), and therefore can hardly be leveraged by nontechnical users.<\/p>\n<p><center><a href=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2010\/12\/Responsibility-for-the-quality-of-data.png\"><img decoding=\"async\" src=\"https:\/\/www.altoros.com\/blog\/wp-content\/uploads\/2010\/12\/Responsibility-for-the-quality-of-data-1024x690.png\" width=\"720\" class=\"aligncenter size-large wp-image-64462\" \/><\/a><small>The parties responsible for data quality (<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>For more best practices on implementing business rules for improving data quality, check out these <a href=\"https:\/\/www.iqint.org\/publication2011\/loshin-2005-04.shtml\" rel=\"noopener noreferrer\" target=\"_blank\">best practices<\/a> and <a href=\"https:\/\/tdwi.org\/~\/media\/TDWI\/TDWI\/Research\/10M\/2005\/TenMistakes_Q3_05.ashx\" rel=\"noopener noreferrer\" target=\"_blank\">10 mistakes to avoid<\/a> from <a href=\"https:\/\/www.linkedin.com\/in\/david-loshin-4a961\/\" rel=\"noopener noreferrer\" target=\"_blank\">David Loshin<\/a>.<\/p>\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\/zVAV4gvx1bceai\" width=\"595\" height=\"485\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" style=\"border:0px solid #CCC; border-width:0px; margin-bottom:5px; max-width: 100%;\" allowfullscreen> <\/iframe><\/center><\/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\/sources-of-poor-data-quality\/\">The Reasons for Poor Data Quality<\/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\/ekaterina\/\">Katherine Vasilega<\/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>(Featured image credit)<\/p>\n<p>&nbsp;<\/p>\n<p>Quality metrics and thresholds<\/p>\n<p>Data integration experts consider information quality the main attribute for business users. Not only does the user need information to be delivered on time, but he or she also wants this information to be of a certain quality. Thus, data quality criteria are required to [&#8230;]<\/p>\n","protected":false},"author":59,"featured_media":62917,"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-48615","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>Implementing a Business Rules\u2013Based Approach to Data Quality | Altoros<\/title>\n<meta name=\"description\" content=\"Read about the techniques a data integration specialist can adopt to improve the quality of corporate information, bringing more value to business users.\" \/>\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\/business-rules-for-data-quality\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Implementing a Business Rules\u2013Based Approach to Data Quality | Altoros\" \/>\n<meta property=\"og:description\" content=\"(Featured image credit) &nbsp; Quality metrics and thresholds Data integration experts consider information quality the main attribute for business users. 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