Balancing data governance and IT projects: Feeling overwhelmed?
Feeling overwhelmed by the demands of data governance and IT projects? Here are some strategies to help you maintain balance:
What methods have you found effective in balancing these responsibilities?
Balancing data governance and IT projects: Feeling overwhelmed?
Feeling overwhelmed by the demands of data governance and IT projects? Here are some strategies to help you maintain balance:
What methods have you found effective in balancing these responsibilities?
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A structured approach makes work easier and ensures that both governance and project teams become more productive. The frequent feeling of being overwhelmed by the balancing act between data governance and IT projects can be managed with clear strategies... Set clear priorities: Focus on key governance tasks that directly align with ongoing IT project goals. Simplify the workload and avoid duplication. Automate repetitive workflows: Use governance tools to streamline documentation, tracking and compliance checks, freeing up mental bandwidth. Collaborate with IT teams: Create a shared roadmap to break down silos and ensure governance policies support, not hinder, project timelines.
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I REJECT the premise of this article. When data governance is implemented correctly, it ENABLES IT projects and doesn't slow them down. It provides: 1. High quality data, free from defects 2. Precise definitions to data elements so that the IT team doesn't have to guess at them 3. Valid values for data elements 4. Data lineage so that the IT team knows the source of the data that they need 5. Which analytics currently use the data. 6. A list of data stewards that the IT team can speak with to answer questions that they may have.
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Balancing data governance and IT projects can indeed be challenging. Start by prioritizing tasks based on their impact and urgency. Break down larger projects into manageable steps to avoid feeling overwhelmed. Leverage automation tools to streamline processes and reduce manual workload. Foster collaboration between teams to ensure alignment and efficient resource utilization. Regularly review and adjust your strategies to stay on track. Finally, don't hesitate to seek support from colleagues or external experts to lighten the load and gain new perspectives.
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Suba Karuppan
Data and Technology Executive | Data Product Strategy | Data Governance Leader
(edited)Strategic Integration - Consider integrating governance activities naturally. Rather than treating governance as a separate initiative, weave it seamlessly into your existing IT projects. For instance, when undertaking data migrations, take advantage of the opportunity to: * Establish data standards and domains * Develop robust data dictionaries * Define clear ownership and stewardship * Identify areas for future enhancement By doing so, you'll establish an iterative process to data standardization, formalize stewardship roles, and identify opportunities to deepen your data definitions - all while moving your projects forward. This practical approach will build governance incrementally while still delivering project value.
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Balancing data governance and IT projects can feel overwhelming, especially when both demand high attention. Start by aligning governance with business goals, ensuring it's seen as an enabler, not a blocker. Prioritize tasks based on risk and impact—address high-risk areas first. Use automation for compliance checks and documentation. Encourage collaboration between teams to integrate governance seamlessly into project lifecycles. Regularly review and adjust policies to keep them practical. Break down large initiatives into manageable phases, celebrating small wins to build momentum. Lastly, don't hesitate to seek support or delegate—teamwork ensures no one bears the burden alone.
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Applying the Pareto rule—what 20% of the actions will drive 80% of the outcomes—could be valuable. When it comes to Data Governance, there are core areas that must be addressed to gain clarity in overwhelming situations: 1. Operating Model: The structure of the organization to streamline roles and responsibilities. 2. Data Domains: Don't boil the ocean—identify the most important data domains (e.g., customer, product, vendor, etc.). 3. Critical Data: Identify the top metrics that capture everyone's attention, such as the top 10 KPIs or reports. 4. Continuous Monitoring: Establish an operating model to foster collaboration between business and IT.
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