{"id":28,"date":"2010-12-23T22:57:36","date_gmt":"2010-12-23T17:27:36","guid":{"rendered":"http:\/\/www.jkspeaks.com\/wordpress\/?p=28"},"modified":"2026-07-05T13:13:14","modified_gmt":"2026-07-05T18:13:14","slug":"data-governance-a-beginners-approach-to-level-2-implementation","status":"publish","type":"post","link":"https:\/\/www.jkspeaks.com\/wordpress\/ai-data\/data-governance-a-beginners-approach-to-level-2-implementation\/","title":{"rendered":"Data Governance: A beginner’s approach to Level-2 implementation"},"content":{"rendered":"\n

The 3-Level approach<\/strong>
The 3-level approach (Figure 1) works well when the organization is serious, has the required funding, has resources to execute, and has a mature Enterprise Information Management (EIM) setup.<\/p>\n\n\n

\n
\"\"<\/a><\/figure>\n<\/div>\n\n\n

In organizations where the IT team is pressurized to show tangible output for every penny invested, a 4-level approach as shown in Figure 2 can be adopted. The question, \u201cIs it possible to divide this further into multiple levels?\u201d might arise. The thumb rule is the more levels there are, the less (substantial) tangible benefit a business can see at every stage. So a faster turn-around with visible progress should be the mantra for a successful implementation.<\/p>\n\n\n

\n
\"\"<\/a><\/figure>\n<\/div>\n\n\n

The four-level data governance implementation has been considered for this article, as that\u2019s more common in the industry today.<\/p>\n\n\n\n

What do we need for level 2?<\/strong>
To set up a \u2018very basic\u2019 DG practice leveraging the existing setup, a database with a few tables, some scripts to act as a trigger, and an intranet portal should suffice. Note that this is just a starting point, and hence the focus would be on data quality and not data governance to begin with. As funds flow in, one can move from data quality monitoring to data quality control and from there to data governance.<\/p>\n\n\n\n

Going online<\/strong>
The organization’s existing intranet portal would be leveraged, and the objective now is to take processes online one by one, starting with the change management process. As part of Level-1 activities, the DG team would have already defined the process for change management, and this would be used now. Steps to convert this process into something that can be monitored are as follows:<\/p>\n\n\n\n

    \n
  • Capture key fields to be used in the form. Example: Ticket ID, priority of change request, source & target systems affected, change description, etc.<\/li>\n\n\n\n
  • Design the form front end with the fields identified and link this with a database (MS Access, Oracle, or MS SQL) at the backend. Mature organizations can leverage their SOA setup<\/li>\n\n\n\n
  • Define the process flow. For example, who raises the request, what happens next, who approves it, exceptions handling, etc. This detail would again come from the detail captured in the previous phase<\/li>\n\n\n\n
  • Now bring in the governance component to ensure that no change gets moved to production without going through this process<\/li>\n<\/ul>\n\n\n
    \n
    \"\"<\/figure>\n<\/div>\n\n\n

    <\/span><\/p>\n\n\n\n

    More the detail captured in step a, tighter will be the governance in step d. For example, if there is a field to capture the results of QA, automatically it will imply that the change that is moving to production has to move through QA (Dev\u2013QA\u2013Production). Assuming the process has been defined to ensure QA compliance for approval of the change request. Step c, which talks about defining process flow, can be accomplished using database triggers and\/or procedures. If the organization already has a rule engine in place, it can be leveraged here.<\/p>\n\n\n\n

    As part of enhancement, this setup can be improved by addition of small bits like SLA tracking, report generation capability, etc. Report generation capability can help governance in a major way by helping the DG team to track various critical parameters like open requests, SLA breaches, requests moved to production through exception process, etc. This in turn will help the DG team to fine-tune processes and improve their maturity.<\/p>\n\n\n\n

    Moving ahead and taking another process online, say, BI tools & technology control. The steps shown in figure 3 are applicable here also. The difference would be in steps c and d, where the process is defined and governed.<\/p>\n\n\n\n

    Some of the other processes that can be brought under governance control without too much cost and effort are the following:<\/p>\n\n\n\n

      \n
    • Database-related activities (e.g., new DB creation, index creation)<\/li>\n\n\n\n
    • Data quality dashboard (e.g., rejected records list pulled from ETL, data certification status)<\/li>\n\n\n\n
    • Data security (e.g., user access to systems)<\/li>\n\n\n\n
    • Training tracker<\/li>\n<\/ul>\n\n\n\n

      In addition to this, various database triggers can be set to increase response levels. The primary advantage of getting to this stage is that the users would now be conversant with various processes in the organization and adapted to them. Some amount of governance would also have been established to move to the next level.<\/p>\n\n\n\n

      What next?<\/strong>
      The organization can now consider moving to the next level by creating self-healing mechanisms wherever applicable. More advanced tools, like, say, Kalido, can be considered if required to improve the DG maturity level.<\/p>\n\n\n\n

      #DataGovernance<\/p>\n","protected":false},"excerpt":{"rendered":"

      The 3-Level approachThe 3-level approach (Figure 1) works well when the organization is serious, has the required funding, has resources to execute, and has a mature Enterprise Information Management (EIM) setup. In organizations where the IT team is pressurized to show tangible output for every penny invested, a 4-level approach as shown in Figure 2…<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_kad_post_transparent":"","_kad_post_title":"","_kad_post_layout":"","_kad_post_sidebar_id":"","_kad_post_content_style":"","_kad_post_vertical_padding":"","_kad_post_feature":"","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[21],"tags":[229,8],"class_list":["post-28","post","type-post","status-publish","format-standard","hentry","category-ai-data","tag-approach","tag-data-governance"],"acf":{"phase":"1","cluster":"Technical","topics":["Data Governance","Frameworks"]},"_links":{"self":[{"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/posts\/28","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/comments?post=28"}],"version-history":[{"count":3,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/posts\/28\/revisions"}],"predecessor-version":[{"id":1233,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/posts\/28\/revisions\/1233"}],"wp:attachment":[{"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/media?parent=28"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/categories?post=28"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.jkspeaks.com\/wordpress\/wp-json\/wp\/v2\/tags?post=28"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}