Last updated on 2024年8月23日

You're torn between data governance and other business objectives. How do you find the right balance?

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As you navigate the complex landscape of modern business, you're often faced with the challenge of aligning data governance with other critical business objectives. It's a delicate balancing act, ensuring that the management of data assets doesn't overshadow the pursuit of innovation, growth, and operational efficiency. Data governance involves establishing policies, procedures, and standards to manage and use data effectively, which is essential for compliance, quality, and security. Yet, it can sometimes seem at odds with the need for agility and quick decision-making in other business areas. The key is to find a synergy between these seemingly contrasting priorities.

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Thomas Kelly

Knowledge graphs, ontology engineering
Kumar Salem Nagarajan

Data & Analytics AI
Mohammed Irfan CDMP, PSMII

Data architect with expertise in data management, data modeling, data quality, data governance, integration, ETL and…

1 Understanding Needs

To strike the right balance, you must first thoroughly understand the specific needs and objectives of your business. This means assessing what data governance can bring to the table in terms of risk management and regulatory compliance, and how it can support other business goals like customer satisfaction and market competitiveness. The goal is not to prioritize one over the other but to recognize that robust data governance can actually empower your business strategies by providing reliable data, reducing risks, and ensuring that data-related decisions are made with a clear understanding of their impact.

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Thomas Kelly

Knowledge graphs, ontology engineering
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Data governance should enable business, not impede its agility and drive. Its principles and practices should act like a traffic light -- manage the flow so that everyone keeps moving, with minimal delays. Frequently revisit and finetune practices that are challenged by new requirements, keeping them aligned with the business and relevant to evolving needs.

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Dario Mangano

Award-Winning CIO | Expert in IT & Business Transformation | Data Strategy Leader | Driving Innovation through Business Intelligence & Data Management
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To balance data governance with other business objectives, start by aligning both with your overall strategic goals. Prioritize data governance as a foundation for long-term success, but ensure it supports agility and innovation rather than hindering it. Involve key stakeholders to understand their needs and demonstrate how strong data governance enhances decision-making, compliance, and efficiency. Use a risk-based approach to focus governance efforts where they have the most impact, and continuously monitor and adjust the balance as business priorities evolve. Communication and flexibility are key to maintaining harmony between governance and other objectives.

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Shazad Mohammed

Deputy General Manager-Data Governance and Migration at _VOIS
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Ensure that your data governance initiatives support and enhance your business objectives. Evaluate the potential impact of data governance initiatives and other business objectives. Embed data governance practices into existing business processes rather than treating them as separate activities. Continuously monitor the progress of both data governance initiatives and other business objectives.

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Kumar Salem Nagarajan

Data & Analytics AI
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Business objectives can bring market competitiveness but to get a sustainable regulatory compliance and customer satisfaction DG office becomes essential need for reducing risks and ensuring data quality across each department.

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2 Setting Priorities

Once you've identified your business needs, setting priorities becomes crucial. You have to decide which aspects of data governance are non-negotiable due to legal or compliance requirements and which can be adjusted to better align with business objectives. Prioritizing doesn't mean compromising on data governance; rather, it's about finding the most efficient ways to integrate it into your business processes so that it supports rather than hinders your objectives.

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Stephan Bouwer

Collibra Developer
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What's the most important thing... Will this current problem still be my problem in 2 to 3 years when I get a promotion? If yes, then focus on solving the problem the right way. If you are going to be somewhere else, solve the problem the quikc way. Priroty number one is always your own job and where you want to be. I forgot what this topic was about but I don't think my answer is really related to data governance at this point. Everyone is anyways just posting AI generated answers here anyways...

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3 Establishing Frameworks

A well-defined data governance framework can serve as the backbone for maintaining this balance. It should be flexible enough to adapt to changing business needs while still upholding data standards. By establishing clear roles, responsibilities, and processes for data management, you can ensure that data governance becomes a natural part of business operations, facilitating rather than impeding progress.

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Kumar Salem Nagarajan

Data & Analytics AI
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Tools and well-established framework becomes an essential services for any data governance initiatives. To scale business operations and facilitate external vendor dataset adoption, comprehensive tools and standards to be established and governed by key stakeholders in the department.

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4 Integrating Processes

Integration is key to balancing data governance with business objectives. Look for opportunities to embed data governance processes within existing workflows to enhance efficiency. This could mean incorporating data quality checks into the data entry process or ensuring that new projects have data compliance built in from the outset. By making data governance an integral part of everyday business activities, it becomes less of a standalone task and more of a value-add to your overall strategy.

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5 Measuring Success

To maintain the balance, it's important to measure the success of your data governance initiatives against your business objectives. This involves setting up metrics that reflect both the health of your data governance practices and their contribution to achieving business goals. Regularly reviewing these metrics can help you adjust your approach as needed and ensure that data governance remains aligned with your business priorities.

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6 Continuous Improvement

Lastly, finding the right balance is an ongoing process. The business environment is dynamic, and so are the challenges associated with data governance. Embrace a culture of continuous improvement, regularly revisiting your strategies, and being open to changes that can enhance both data governance and business performance. This will help you stay agile and responsive to new opportunities and challenges as they arise.

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Mohammed Irfan CDMP, PSMII

Data architect with expertise in data management, data modeling, data quality, data governance, integration, ETL and database management. Bigdata | Teradata | Ab initio.
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John found himself torn between driving data governance initiatives and meeting other pressing business objectives. * To strike a balance, he engaged with key stakeholders across departments, emphasizing how data governance could support their goals rather than hinder them. * By aligning data governance strategies with broader business priorities, he demonstrated that quality data was the foundation for growth and decision-making. * John also adopted a phased approach, gradually integrating governance practices into existing workflows without disrupting ongoing projects. The result? A win-win scenario where both governance and business objectives advanced in harmony.

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You're torn between data governance and other business objectives. How do you find the right balance?

1

2

3

4

5

6

1 Understanding Needs

2 Setting Priorities

3 Establishing Frameworks

4 Integrating Processes

5 Measuring Success

6 Continuous Improvement

Data Governance

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You're torn between data governance and other business objectives. How do you find the right balance?

1

2

3

4

5

6

1 Understanding Needs

2 Setting Priorities

3 Establishing Frameworks

4 Integrating Processes

5 Measuring Success

6 Continuous Improvement

Data Governance

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感谢您的反馈

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