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Last updated on 2024年9月16日

Balancing control and flexibility in data governance: Are you prepared to navigate conflicting needs?

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In the fast-paced world of data management, striking the right balance between control and flexibility is critical. As you navigate the complex landscape of data governance, you may find yourself wrestling with the need to maintain strict data quality and security while also allowing for the agility required to respond to new opportunities and challenges. This balancing act is not just about following best practices; it's about understanding the unique needs of your organization and adapting your governance strategies accordingly. By preparing to manage these conflicting needs, you can ensure that your data governance framework supports both the protection and the innovative use of your data assets.

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Ashish Singh

Visionary Senior Leader | Data Engineering | Data Analytics | Data Governance | GenAI | Speaker | Ex Yahoo, Credit…
Abhilash Nagilla

Empowering Customers on Their Cloud Data Journey

1 Core Principles

The bedrock of any data governance strategy lies in its core principles. These principles should reflect your organization's values and objectives, guiding how data is managed and used. Establishing clear guidelines for data access, quality, and security is essential, but so is leaving room for context-driven decision-making. By setting foundational policies that are both robust and adaptable, you create a framework that can evolve with your organization's needs without compromising on accountability or compliance.

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Ashish Singh

Visionary Senior Leader | Data Engineering | Data Analytics | Data Governance | GenAI | Speaker | Ex Yahoo, Credit Suisse, UBS
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To navigate conflicting needs, I've relied on core principles: Clear Data Ownership: Define who owns data and their responsibilities for its quality and security. Consistent Standards: Establish standardized guidelines for data creation, storage, and usage. Scalable Frameworks: Develop adaptable governance structures that can evolve with your organization. Risk-Based Approach: Prioritize data governance efforts based on risk levels, focusing on critical assets. Empowerment with Accountability: Grant data access and autonomy while maintaining accountability. By adhering to these principles, organizations can create a data governance environment that supports innovation while safeguarding data integrity and security.

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Abhilash Nagilla

Empowering Customers on Their Cloud Data Journey
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Establishing clear guidelines around data access, quality, and security is essential, but the framework also needs adaptability to support evolving business needs. By striking this balance between robust policies and context-driven decision-making, companies create a data governance model that maintains accountability and compliance while enabling the strategic use of data.

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2 Data Stewardship

Data stewardship is the application of your governance policies in the day-to-day management of data. It involves assigning responsibilities to individuals or teams who ensure data accuracy, accessibility, and proper use. Effective stewards act as the bridge between rigid control and necessary flexibility, making judgment calls that align with governance policies while considering the nuances of each situation. Empowering stewards with the right tools and authority is key to maintaining this balance.

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3 Technology Tools

Technology plays a pivotal role in achieving a balance in data governance. Utilizing the right software and tools can automate compliance checks, streamline data quality processes, and provide real-time monitoring. This automation supports a high level of control without stifling flexibility, as it allows for rapid adjustments and provides insights that can inform more nuanced governance decisions. Carefully select technologies that align with your governance goals and can adapt to changing needs.

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Abhilash Nagilla

Empowering Customers on Their Cloud Data Journey
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When implemented effectively, technology allows for rapid adjustments to governance policies and provides valuable insights that can inform more subtle decision-making. Customer can get both agility and governance without any compromises made.

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4 Risk Management

Risk management is an integral part of data governance, as it helps identify potential threats to data integrity and security. Balancing control with flexibility means understanding which risks are acceptable and which require more stringent controls. It's about not just mitigating risks but also recognizing opportunities where a more flexible approach could lead to innovation and growth. A well-crafted risk management strategy will enable you to make informed decisions about when to tighten controls and when to allow for more freedom.

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Abhilash Nagilla

Empowering Customers on Their Cloud Data Journey
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A well-architected risk management strategy empowers data users to leverage data strategically, while maintaining the necessary safeguards to ensure compliance and protect against threats. Integrating risk management into the core of data governance creates a framework that is both robust and agile.

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5 Training & Culture

Creating a culture that values both control and flexibility in data governance is vital. Training programs should not only cover the technical aspects of data management but also emphasize the importance of judgment and adaptability within the governance framework. Encourage a culture where questioning and improving upon existing processes is welcomed, as this will foster an environment where balance can be achieved naturally.

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Abhishek Ray

Enterprise Data Strategy Practice @ Capgemini Invent
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?? ???????? ????????????????????: Effective data governance requires balancing strict control to ensure data quality, compliance, and security, with the flexibility to foster innovation and quick decision-making. ?? ????????????????: Comprehensive training programs are essential to educate employees on governance principles, the importance of flexibility, and how to navigate grey areas where judgment is required. ?? ?????????????????????????? ??????????????: A supportive organizational culture that encourages collaboration between business and IT ensures governance policies are both practical and adaptable to changing business needs.

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6 Continuous Evolution

Finally, remember that data governance is not a set-and-forget system; it requires continuous evolution. Regularly review and update your governance framework to reflect new technologies, market conditions, and business objectives. This iterative process will help you maintain a balance between control and flexibility, ensuring that your data governance strategy remains effective and relevant over time.

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Balancing control and flexibility in data governance: Are you prepared to navigate conflicting needs?

1

2

3

4

5

6

1 Core Principles

2 Data Stewardship

3 Technology Tools

4 Risk Management

5 Training & Culture

6 Continuous Evolution

Data Governance

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Balancing control and flexibility in data governance: Are you prepared to navigate conflicting needs?

1

2

3

4

5

6

1 Core Principles

2 Data Stewardship

3 Technology Tools

4 Risk Management

5 Training & Culture

6 Continuous Evolution

Data Governance

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