{"id":479,"date":"2018-08-02T18:20:02","date_gmt":"2018-08-03T01:20:02","guid":{"rendered":"http:\/\/www.lightsondata.com\/?p=479"},"modified":"2020-09-06T22:06:52","modified_gmt":"2020-09-07T05:06:52","slug":"3-data-quality-projects-data-steward-should-work-on","status":"publish","type":"post","link":"https:\/\/www.lightsondata.com\/3-data-quality-projects-data-steward-should-work-on\/","title":{"rendered":"3 types of data quality projects a data steward should work on"},"content":{"rendered":"<p>In\u00a0\u00a0&#8220;<a href=\"https:\/\/www.lightsondata.com\/the-trifecta-of-the-best-data-quality-management\/\" target=\"_blank\" rel=\"noopener noreferrer\">The trifecta of the best data quality management<\/a>&#8221; article, I&#8217;ve addressed why a data quality program is needed and what\u00a0the recurring steps you should always go through are\u00a0in order to carry on continuous and sustainable efforts to improve and\/ or maintain the quality of your data. When it comes to working with the data itself, there are 3 main projects every data steward should tackle:<\/p>\n<h2>1. Data quality assessment project<\/h2>\n<p><strong>Data Quality Management Phase:<\/strong>\u00a0\u00a0Analyze &amp; Identify (Phase I)<\/p>\n<p><strong>Purpose:<\/strong> To quantitatively, qualitatively, objectively understand the state of data quality<\/p>\n<p><strong>Assumptions:<\/strong><\/p>\n<ul>\n<li>A particular set of data has been chosen<\/li>\n<li>The business need and impact is understood<\/li>\n<li>Data ownership is assigned<\/li>\n<li>Project sponsorship is in place<\/li>\n<\/ul>\n<p><strong>Expected results and deliverables:<\/strong><\/p>\n<ul>\n<li>A data quality scorecard with initial scores<\/li>\n<li>Data quality scripts<\/li>\n<li>True cost of data quality improvements and ROI calculations<\/li>\n<\/ul>\n<p><strong>High level components:<\/strong><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" data-attachment-id=\"485\" data-permalink=\"https:\/\/www.lightsondata.com\/3-data-quality-projects-data-steward-should-work-on\/assessment-project\/\" data-orig-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/assessment-project.jpg?fit=717%2C169&amp;ssl=1\" data-orig-size=\"717,169\" data-comments-opened=\"1\" data-image-meta=\"{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;0&quot;}\" data-image-title=\"assessment project\" data-image-description=\"\" data-image-caption=\"\" data-medium-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/assessment-project.jpg?fit=300%2C71&amp;ssl=1\" data-large-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/assessment-project.jpg?fit=717%2C169&amp;ssl=1\" class=\"wp-image-485 aligncenter size-full\" src=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/assessment-project.jpg?resize=717%2C169\" alt=\"assessment project\" width=\"717\" height=\"169\" srcset=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/assessment-project.jpg?w=717&amp;ssl=1 717w, https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/assessment-project.jpg?resize=300%2C71&amp;ssl=1 300w, https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/assessment-project.jpg?resize=600%2C141&amp;ssl=1 600w\" sizes=\"auto, (max-width: 717px) 100vw, 717px\" \/><\/p>\n<ol>\n<li>Plan &#8211; Identify and secure necessary resources and create a project plan for a particular data set.<\/li>\n<li>Build DQ rules &#8211;\u00a0Use a data quality tool or a query script (ex: SQL procedure) to\u00a0convert business rules into data quality rules.<\/li>\n<li>Execute DQ rules &#8211; Run the tool\u00a0or script and save the output.<\/li>\n<li>Test and improve &#8211;\u00a0Work with the business and data experts to evaluate the results and see if the data quality scripts needs to be tweaked.<\/li>\n<li>Store DQ results &#8211;\u00a0Create the scorecard and populate it with the snapshot of your data quality metrics. Recording the baseline of your data quality status is one of the most important steps people forget to take.<\/li>\n<li>Evaluate &amp; improve &#8211;\u00a0Evaluate your findings, the process itself, resources needed, the entire workflow and process, overall work and\u00a0experience and see how it could be improved for future similar data quality assessment projects. At this step, you should also calculate the cost and benefits of cleansing this data.<\/li>\n<li>\u00a0Communicate &#8211;\u00a0In my best data quality management practices, communication is always a critical step to have. This is not sequential to all previous steps. Instead, it should occur prior, during, and after each step in order to increase visibility and gain stakeholder support for your data quality efforts. Don&#8217;t overlook its importance.<\/li>\n<\/ol>\n<p><strong>Stakeholders:<\/strong> Data owners, consumers, and data stewards<\/p>\n<p><strong>Implementation team:<\/strong> IT developers, subject matter experts (technical and business), data custodians<\/p>\n<hr \/>\n<h3 style=\"text-align: center;\"><em>If you want to know about the <a href=\"https:\/\/www.lightsondata.com\/understanding-data-stewardship-types\/\" target=\"_blank\" rel=\"noopener noreferrer\">different types of a data steward<\/a>, please read our other article, too.<\/em><\/h3>\n<hr \/>\n<h2>2. Data cleansing project<\/h2>\n<p><strong>Data Quality Management Phase:<\/strong>\u00a0\u00a0Fix &amp; Prevent (Phase II)<\/p>\n<p><strong>Purpose:<\/strong> To correct any data quality issues<\/p>\n<div class=\"tve_content_lock tve_lock_hide tve_lead_lock\">\n                <div class=\"tve_lead_lock_shortcode\"><span style=\"--tl-form-height-m:422.844px;--tl-form-height-t:361.878px;--tl-form-height-d:361.878px;\" class=\"tl-placeholder-f-type-shortcode_2273 tl-preload-form\"><span><\/span><\/span><\/div>\n                <div class=\"tve_lead_locked_content\"><div class=\"tve_lead_locked_overlay\"><\/div>\n<p><strong>Assumptions:<\/strong><\/p>\n<ul>\n<li>A baseline measurement has been taken<\/li>\n<li>Data stewardship is assigned<\/li>\n<li>Project sponsorship is in place<\/li>\n<\/ul>\n<p><strong>Expected results and deliverables:<\/strong><\/p>\n<ul>\n<li>Data cleansing process and data cleansing scripts<\/li>\n<li>Improved data quality<\/li>\n<li>Data change audit trail<\/li>\n<\/ul>\n<p><strong>High level components:<\/strong><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" data-attachment-id=\"487\" data-permalink=\"https:\/\/www.lightsondata.com\/3-data-quality-projects-data-steward-should-work-on\/data-cleansing-project\/\" data-orig-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/data-cleansing-project.jpg?fit=602%2C134&amp;ssl=1\" data-orig-size=\"602,134\" data-comments-opened=\"1\" data-image-meta=\"{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;0&quot;}\" data-image-title=\"data cleansing project\" data-image-description=\"\" data-image-caption=\"\" data-medium-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/data-cleansing-project.jpg?fit=300%2C67&amp;ssl=1\" data-large-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/data-cleansing-project.jpg?fit=602%2C134&amp;ssl=1\" class=\"wp-image-487 aligncenter size-full\" src=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/data-cleansing-project.jpg?resize=602%2C134\" alt=\"data cleansing project\" width=\"602\" height=\"134\" srcset=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/data-cleansing-project.jpg?w=602&amp;ssl=1 602w, https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/data-cleansing-project.jpg?resize=300%2C67&amp;ssl=1 300w, https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/data-cleansing-project.jpg?resize=600%2C134&amp;ssl=1 600w\" sizes=\"auto, (max-width: 602px) 100vw, 602px\" \/><\/p>\n<ol>\n<li>Plan &#8211; Identify and secure necessary resources and create a project plan for cleansing this data. This will look different if you need to purchase any 3rd data services or sources to validate against.<\/li>\n<li>Prepare data &#8211;\u00a0Sometimes, the decision is made to only cleanse a subset of the same data set (such as only your residential national addresses). The data might also need to be extracted out of your database to pass on to a 3rd party data service and this is the step this is tackled.<\/li>\n<li>Develop scripts &#8211;\u00a0Build your in-house data cleansing scripts (usually repurposing the work done in the data assessment project), and\/or creating the technical procedures for loading the cleansed data back into your database. Test and improve until you comply with your data quality rules.<\/li>\n<li>Cleanse &#8211; Run your scripts and cleanse the data.<\/li>\n<li>Handle exceptions &#8211;\u00a0You should always expect encountering exceptions and not be able to cleanse all of your desired data. This step could trigger the start of other data quality projects, postpone this work and push these data in an exception table, or redevelop your data cleansing scripts to resolve them if possible.<\/li>\n<li>\u00a0Communicate &#8211;\u00a0Same as in any other project, make sure you communicate at every step. If you&#8217;re worried about communication overload you can just communicate at the beginning of this project of its intention and its outcome at the end.<\/li>\n<\/ol>\n<p><strong>Stakeholders:<\/strong> Data owners, consumers, and data stewards<\/p>\n<p><strong>Implementation team:<\/strong> IT developers, subject matter experts (technical and business), data custodians<\/p>\n<hr \/>\n<h2><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" data-attachment-id=\"494\" data-permalink=\"https:\/\/www.lightsondata.com\/3-data-quality-projects-data-steward-should-work-on\/img_2367\/\" data-orig-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/img_2367-e1533321030905.jpg?fit=1057%2C823&amp;ssl=1\" data-orig-size=\"1057,823\" data-comments-opened=\"1\" data-image-meta=\"{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;1&quot;}\" data-image-title=\"img_2367\" data-image-description=\"\" data-image-caption=\"\" data-medium-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/img_2367-e1533321030905.jpg?fit=300%2C234&amp;ssl=1\" data-large-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/img_2367-e1533321030905.jpg?fit=1024%2C797&amp;ssl=1\" class=\"aligncenter size-large wp-image-494\" src=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/img_2367-e1533321030905-1024x797.jpg?resize=940%2C732\" alt=\"\" width=\"940\" height=\"732\" srcset=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/img_2367-e1533321030905.jpg?resize=1024%2C797&amp;ssl=1 1024w, https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/img_2367-e1533321030905.jpg?resize=300%2C234&amp;ssl=1 300w, https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/img_2367-e1533321030905.jpg?resize=768%2C598&amp;ssl=1 768w, https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/img_2367-e1533321030905.jpg?resize=600%2C467&amp;ssl=1 600w, https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/img_2367-e1533321030905.jpg?w=1057&amp;ssl=1 1057w\" sizes=\"auto, (max-width: 940px) 100vw, 940px\" \/><\/h2>\n<h2>3.\u00a0Bad data prevention\u00a0project<\/h2>\n<p><strong>Data Quality Management Phase:<\/strong>\u00a0\u00a0Fix &amp; Prevent (Phase II)<\/p>\n<p><strong>Purpose:<\/strong> To prevent or reduce any similar data quality issues reoccurring in the future<\/p>\n<p><strong>Assumptions:<\/strong><\/p>\n<ul>\n<li>Data quality issues have been identified<\/li>\n<li>The scope of bad data prevention has been defined<\/li>\n<li>Data stewardship is assigned<\/li>\n<li>Project sponsorship is in place<\/li>\n<\/ul>\n<p><strong>Expected results and deliverables:<\/strong><\/p>\n<ul>\n<li>Alignment between data quality and business needs<\/li>\n<li>Improved data quality<\/li>\n<li>Reduced cost of performing data cleansing<\/li>\n<\/ul>\n<p><strong>High level components:<\/strong><\/p>\n<p><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" data-attachment-id=\"486\" data-permalink=\"https:\/\/www.lightsondata.com\/3-data-quality-projects-data-steward-should-work-on\/bad-data-prevention\/\" data-orig-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/bad-data-prevention.jpg?fit=604%2C162&amp;ssl=1\" data-orig-size=\"604,162\" data-comments-opened=\"1\" data-image-meta=\"{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;0&quot;}\" data-image-title=\"bad data prevention\" data-image-description=\"\" data-image-caption=\"\" data-medium-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/bad-data-prevention.jpg?fit=300%2C80&amp;ssl=1\" data-large-file=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/bad-data-prevention.jpg?fit=604%2C162&amp;ssl=1\" class=\"wp-image-486 aligncenter size-full\" src=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/bad-data-prevention.jpg?resize=604%2C162\" alt=\"bad data prevention\" width=\"604\" height=\"162\" srcset=\"https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/bad-data-prevention.jpg?w=604&amp;ssl=1 604w, https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/bad-data-prevention.jpg?resize=300%2C80&amp;ssl=1 300w, https:\/\/i0.wp.com\/www.lightsondata.com\/wp-content\/uploads\/2018\/08\/bad-data-prevention.jpg?resize=600%2C161&amp;ssl=1 600w\" sizes=\"auto, (max-width: 604px) 100vw, 604px\" \/><\/p>\n<ol>\n<li>Plan &#8211; Identify and secure necessary resources and create a project plan<\/li>\n<li>Analyze causes &#8211;\u00a0Your business and technical analysts need to help you on this step. What is the root cause that is creating the data quality issues, or is it more than one? Is it\u00a0due to a\u00a0lack of standards and definitions, misalignment between the business needs and the technical implementation, are there technical limitations?<\/li>\n<li>Determine Solutions &#8211;\u00a0Depending on the root causes, you might need to create a new ETL process, change a piece in the data architecture,\u00a0update an existing business process to reduce certain ambiguity which might be creating bad data, implement data quality controls at point of entry, change existing\u00a0standards, or just communicate requirements better. This own step is a topic on its own.<\/li>\n<li>Implement Solutions &#8211; Develop and deploy whatever solution you&#8217;ve agreed on in the previous step. It&#8217;s usually more than one thing that needs to be done.<\/li>\n<li>Monitor Results &#8211;\u00a0Even if you think you&#8217;ve done everything to prevent the same data quality issues from ever reoccurring, chances are that it will. Always create an audit for your data quality rules to flag any outlier so you can then analyze its cause and implement new solutions. Work on the audit piece should reuse the scripts developed in the assessment and\/or data cleansing projects.<\/li>\n<li>\u00a0Communicate &#8211;\u00a0Keep reminding your stakeholders the importance of keeping your data clean. Always communicate and raise awareness.<\/li>\n<\/ol>\n<p><strong>Stakeholders:<\/strong> Data owners,\u00a0data stewards, business leads, process owners<\/p>\n<p><strong>Implementation team:<\/strong> IT developers, subject matter experts (technical and business process), data custodians, business analysts<\/p>\n<hr \/>\n<p><\/p><\/div>\n            <\/div>\n<p>To reiterate, these 3 projects should be part of\u00a0data quality management and data governance programs. Each project is influenced by the project management methodology you choose to follow, as well as available resources, scope, industry, and organizational culture.<\/p>\n<p>If you are a data steward, you should be part of at least one of these projects. Hopefully this provides you with enough guidance on the steps each project should cover, what stakeholders you should involve, who you should include in your project teams, and what deliverables you should strive for.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In\u00a0\u00a0&#8220;The trifecta of the best data quality management&#8221; article, I&#8217;ve addressed why a data quality program is needed and what\u00a0the recurring steps you should always go through are\u00a0in order to carry on continuous and sustainable efforts to improve and\/ or maintain the quality of your data. When it comes to working with the data itself, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":494,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[4],"tags":[24],"class_list":["post-479","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-quality","tag-data-stewardship","post-wrapper","thrv_wrapper"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>3 types of data quality projects a data steward should work on | LightsOnData<\/title>\n<meta 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