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Last updated on 2024年8月10日

A manager prioritizes speed over data governance. How can you ensure the integrity of your data?

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In today's fast-paced business environment, managers often prioritize speed to stay competitive. However, this can lead to the neglect of data governance, which is crucial for maintaining the integrity and quality of data. Data governance involves the overall management of the availability, usability, integrity, and security of the data employed in an enterprise. Despite the pressure to deliver quickly, you can still uphold data governance by implementing strategic measures to ensure your data remains accurate, consistent, and reliable.

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Axel Schwanke

Senior Data Engineer | Data Architect | Data Science | Data Mesh | Data Governance | 4x Databricks certified | 2x AWS…
Abhijit Joshi

ML | Data Engineering | Mentor | Speaker

1 Prioritize Tasks

To balance speed and data governance , prioritize tasks based on their impact on data integrity . Identify which processes require rigorous checks and which can be streamlined without compromising data quality. By classifying tasks, you can allocate resources effectively, ensuring that critical data governance practices are maintained while meeting deadlines. This strategy helps you focus on areas where data governance is non-negotiable, such as compliance with legal standards and protection of sensitive information .

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Abhijit Joshi

ML | Data Engineering | Mentor | Speaker
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One thing I’ve found helpful is integrating a risk-based approach when prioritizing tasks in data governance. By assessing the potential impact of each task on data integrity, it’s possible to categorize them into high, medium, and low-risk activities. This allows for a more strategic allocation of resources where the highest risks to data integrity are addressed first, ensuring that critical governance measures are not compromised even when speed is a priority

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Tun? SABUNCU

Gouvernance des données & Architecture des données
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Pour garantir l'intégrité des données face à un manager privilégiant la vitesse : 1. Automatisation : Implémentez des contr?les de qualité automatisés. 2. Documentation rapide : Créez des templates pour une documentation efficace. 3. Validation en temps réel : Intégrez des vérifications pendant la saisie/traitement. 4. Formation ciblée : Sensibilisez l'équipe aux risques d'une mauvaise gouvernance. 5. Métriques d'intégrité : établissez des KPIs pour suivre la qualité des données. 6. Approche itérative : Proposez des améliorations progressives de gouvernance. 7. Démonstration de valeur : Montrez comment une bonne gouvernance peut accélérer les projets futurs.

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2 Automate Processes

Automation is your ally in maintaining data integrity. By automating routine data governance tasks such as data quality checks, backups, and access controls, you can reduce human error and free up time for tasks that require human judgment. Tools like data quality management software can continuously monitor and clean your data, ensuring it remains accurate and trustworthy without slowing down your operations.

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Oluwabusayo Adigun, CDMP?,CBAP?

DAMA CDMP? Practitioner|Top Data Governance Voice|Top Data Management Voice|Data Quality|Change Management
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Speed becomes worthless when the output achieved speedily is of poor quality or useless. However, data governance is an enabler of automation because it often involve developing standard processes that are verified, approved, and automated. Automation helps eliminate human errors, and the time required for manual and repetitive tasks is conserved or appropriated to other tasks. Therefore, Data governance directly translates to gaining speed and should be prioritized to achieve speed.

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3 Engage Stakeholders

Engaging stakeholders in the importance of data governance can create a culture that values data integrity. Educate your team on how good data governance practices can lead to better decision-making and long-term benefits for the company. When everyone understands the stakes, they are more likely to take the time to ensure that data is handled correctly, even when under pressure to perform quickly.

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Axel Schwanke

Senior Data Engineer | Data Architect | Data Science | Data Mesh | Data Governance | 4x Databricks certified | 2x AWS certified | 1x CDMP certified | Medium Writer | Turning Data into Business Growth | Nuremberg, Germany
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If a manager prioritizes speed over data management, it's important to focus on stakeholder engagement... Communicate the risks: Explain to all stakeholders the potential risks of neglecting data management, such as data breaches or compliance issues. This will help them understand the long-term impact on the business. Align priorities: Work with stakeholders to strike a balance between speed and necessary data governance procedures. Ensure that governance is integrated into the workflow without significantly delaying progress. Define responsibilities: Assign specific roles responsible for monitoring data quality and governance. This will ensure that data integrity is maintained despite the focus on speed.

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4 Continuous Monitoring

Continuous monitoring of your data ecosystem is crucial for identifying and addressing issues promptly. Implement real-time monitoring systems that can alert you to potential data breaches or inconsistencies. This proactive approach allows you to maintain the integrity of your data without slowing down your operations, as issues can be resolved quickly before they escalate into larger problems.

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5 Validate Regularly

Regular validation of your data ensures that it remains accurate and useful. Schedule frequent validations to check the quality and consistency of your data. This step can be integrated into your regular workflow so that it becomes a part of the process rather than an afterthought. By consistently validating your data, you can catch errors early and maintain the trustworthiness of your datasets.

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6 Educate and Train

Lastly, invest in educating and training your team on best practices for data governance. A well-informed team is less likely to cut corners when it comes to managing data. Provide regular training sessions and resources to keep everyone up-to-date on the latest data governance strategies. This empowers your team to make decisions that align with both the need for speed and the imperative of maintaining data integrity.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Oluwabusayo Adigun, CDMP?,CBAP?

DAMA CDMP? Practitioner|Top Data Governance Voice|Top Data Management Voice|Data Quality|Change Management
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Data Governance is not a barrier to speed. So, I recommend that the manager prioritizes implementing and adhering to data governance to gain speed. In the long run, data governance saves the business from losses, reputational damage, and myriads of data problems, which are the actual barriers to speed.

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A manager prioritizes speed over data governance. How can you ensure the integrity of your data?

1

2

3

4

5

6

7

1 Prioritize Tasks

2 Automate Processes

3 Engage Stakeholders

4 Continuous Monitoring

5 Validate Regularly

6 Educate and Train

7 Here’s what else to consider

Data Governance

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A manager prioritizes speed over data governance. How can you ensure the integrity of your data?

1

2

3

4

5

6

7

1 Prioritize Tasks

2 Automate Processes

3 Engage Stakeholders

4 Continuous Monitoring

5 Validate Regularly

6 Educate and Train

7 Here’s what else to consider

Data Governance

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