Data Governance
Digital Transformation Pro can assist you in developing a governance program that incrementally addresses the technology, process and organizational issues that are critical for success. Our first step is to assess your existing situation in the context of our Governance Maturity Model. We can then establish your target or desired maturity level. An incremental plan is developed to allow for pragmatic investments, often aligned with prioritized projects to attain the target state.
[/fusion_text][/fusion_builder_column][fusion_builder_column type=”3_5″ last=”yes” spacing=”yes” center_content=”no” hide_on_mobile=”no” background_color=”” background_image=”” background_repeat=”no-repeat” background_position=”left top” hover_type=”none” link=”” border_position=”all” border_size=”0px” border_color=”” border_style=”” padding=”” margin_top=”” margin_bottom=”” animation_type=”” animation_direction=”” animation_speed=”0.1″ animation_offset=”” class=”” id=””][fusion_tabs design=”classic” layout=”horizontal” justified=”no” backgroundcolor=”” inactivecolor=”” bordercolor=”” class=”” id=””][fusion_tab title=”Organizational Roadmap” icon=””][fusion_fontawesome icon=”random” circle=”yes” size=”large”/]Provides role definitions, executive sponsorship, identification of the data steward with the business decision-making authority, governance PMO, data quality competence centers and operational models are all part of this domain.[/fusion_tab][fusion_tab title=”Process Roadmap” icon=””][fusion_fontawesome icon=”random” circle=”yes” size=”large”/] Defines governance policies and procedures, data quality processes with metrics for measurement, and business definitions that leverage industry standards as appropriate. The process roadmap also includes enterprise business architecture practices and blueprints, as well as processes for architectural review at the project level.[/fusion_tab][fusion_tab title=”Technology Roadmap” icon=””][fusion_fontawesome icon=”random” circle=”yes” size=”large”/]
Lists criteria for functionalities and the selection of data profiling tools used to assess data quality at a baseline and on-going basis. In addition, the technology roadmap covers data quality tools, master data management solutions, metadata repositories, industry models and taxonomies.[/fusion_tab][/fusion_tabs][/fusion_builder_column][fusion_builder_column type=”1_1″ last=”yes” spacing=”yes” center_content=”no” hide_on_mobile=”no” background_color=”” background_image=”” background_repeat=”no-repeat” background_position=”left top” hover_type=”none” link=”” border_position=”all” border_size=”0px” border_color=”” border_style=”” padding=”” margin_top=”” margin_bottom=”” animation_type=”” animation_direction=”” animation_speed=”0.1″ animation_offset=”” class=”” id=””][fusion_title size=”2″ content_align=”left” style_type=”default” sep_color=”” margin_top=”” margin_bottom=”20px” class=”” id=””]Significant Value[/fusion_title][fusion_text]In many ways, data governance represents a true confluence of business and IT. If properly executed, it offers significant value to the organization, based on:
- Information that is defined and used consistently across the enterprise.
- Increased consumer confidence in data, thereby increasing the use of this data.
- Reduced time-to-market for new data initiatives.
- A framework to inform decision-making as it relates to data management initiatives.