登录查看更多内容

Struggling with IT and business collaboration in data governance?

由人工智能和领英社区提供技术支持

Data governance is a critical aspect of modern businesses, where IT and business units must work hand-in-hand to manage data effectively. However, collaboration between these two entities is often fraught with challenges. The complexities of data management require a unified strategy that aligns with both technical capabilities and business objectives. When IT and business collaborate effectively, they can ensure data quality, compliance, and security, while also unlocking the value of data to drive business decisions and innovation. Understanding the common hurdles in this collaboration is the first step towards a more cohesive data governance approach.

此文章中的业界达人

由社区从 10 条内容中精选。了解更多

Faiza Khalil

MIS, Policy and Project Coordinator at Samba Bank Limited - PMP? Certified From PMI- MBA Finance Gold Medalist
Mukundan A P

??Leadership | ????? AI | ?? Data Scientist | ?? Data-Driven Decision | ?? DBMS | ?? GrowthTech | ?? ?? Strategy |…

1 Common Barriers

Understanding the common barriers to collaboration between IT and business in data governance is essential. Often, there is a fundamental disconnect in how both groups perceive the value and role of data. IT professionals might prioritize system efficiency and data security, whereas business teams may focus on data analytics and insights. These differing priorities can lead to misaligned goals and communication breakdowns. Additionally, a lack of shared language or understanding of technical terms can exacerbate these issues, making it difficult to form a cohesive data governance strategy.

添加您的观点

Faiza Khalil

MIS, Policy and Project Coordinator at Samba Bank Limited - PMP? Certified From PMI- MBA Finance Gold Medalist
举报内容
Struggling with IT and business collaboration in data governance? Align goals, establish clear communication channels, and use frameworks to ensure both IT and business teams understand and contribute effectively.

已翻译

赞
Sidney Dettino Junior

Consultor de Dados e Analytics | Copilot Champion na Petrobras | Power BI Lover | PL-300 | Petrobras | Harvard ManageMentor | FGV
举报内容
A colabora??o entre TI e negócios é dificultada por barreiras organizacionais e culturais, como a falta de alinhamento de prioridades e linguagens. Para superar essas lacunas, é essencial estabelecer uma vis?o compartilhada e alinhar objetivos por meio de workshops colaborativos e treinamentos. A integra??o de ferramentas de comunica??o em tempo real também é crucial. Além disso, é preciso enfrentar desafios como a falta de clareza nas fun??es e responsabilidades, dificuldades de acesso e qualidade dos dados, falta de rotinas de comunica??o eficazes, ausência de patrocinador para governan?a de dados e lacunas no papel do gestor de dados. A colabora??o efetiva entre TI e negócios impulsiona a inova??o e o sucesso organizacional.

已翻译

赞
Mukundan A P

??Leadership | ????? AI | ?? Data Scientist | ?? Data-Driven Decision | ?? DBMS | ?? GrowthTech | ?? ?? Strategy | ???? Strategic Growth | ??B2B Data-Driven Expert | ?? Speaker | ?? Mentor | ?? Youth Service
举报内容
Understanding barriers between IT and business in data governance is crucial. Often, there's a fundamental disconnect in how each group values data. IT focuses on system efficiency ?? and security, while business teams emphasize data analytics ?? and insights. These differing priorities can lead to misaligned goals and communication breakdowns. Additionally, a lack of shared language ??? or understanding of technical terms exacerbates these issues, hindering cohesive data governance strategies.

已翻译

赞

2 Bridging Gaps

To bridge the gaps between IT and business, it's important to establish a common language and set of objectives. This can be achieved by creating cross-functional teams that include members from both sides, fostering an environment where each group can learn from the other's expertise. Regular meetings and workshops can help to align goals and ensure that both IT and business perspectives are considered in the data governance strategy. By working together, these teams can develop a shared vision that balances technical requirements with business needs.

添加您的观点

Sidney Dettino Junior

Consultor de Dados e Analytics | Copilot Champion na Petrobras | Power BI Lover | PL-300 | Petrobras | Harvard ManageMentor | FGV
举报内容
Para superar as barreiras na comunica??o e alinhamento entre TI e negócios, é essencial estabelecer uma estratégia clara de dados com objetivos focados nas necessidades de negócios. Isso inclui reuni?es regulares, equipes multifuncionais, documenta??o de processos, padroniza??o de procedimentos e um "dicionário de dados" comum. Identificar partes interessadas técnicas e de negócios alinhadas com objetivos e vis?o estratégica dos dados é crucial. Métricas bem definidas devem ser estabelecidas para medir o sucesso. Essas a??es promovem colabora??o e preenchem as lacunas existentes.

已翻译

赞
Mukundan A P

??Leadership | ????? AI | ?? Data Scientist | ?? Data-Driven Decision | ?? DBMS | ?? GrowthTech | ?? ?? Strategy | ???? Strategic Growth | ??B2B Data-Driven Expert | ?? Speaker | ?? Mentor | ?? Youth Service
举报内容
To bridge IT and business gaps, establish a common language ??? and set of objectives. Form cross-functional teams ?? with members from both sides to foster mutual learning. Regular meetings and workshops ?? can align goals and ensure all perspectives are integrated into the data governance strategy. By collaborating, teams develop a shared vision that balances technical requirements with business needs, enhancing overall effectiveness.

已翻译

赞

3 Role Clarity

Clarifying the roles and responsibilities of IT and business within data governance is another crucial step. Each group should have a clear understanding of their specific contributions to data management. IT might be responsible for implementing data security measures and maintaining the infrastructure, while business units could focus on data analysis and applying insights to strategic decisions. Clear delineation of these roles can prevent overlap and confusion, leading to more efficient and effective collaboration.

添加您的观点

Sidney Dettino Junior

Consultor de Dados e Analytics | Copilot Champion na Petrobras | Power BI Lover | PL-300 | Petrobras | Harvard ManageMentor | FGV
举报内容
A administra??o efetiva de dados é essencial para gerar valor por meio de Analytics e IA. Isso requer a ado??o de padr?es, políticas e medi??o de resultados, além da democratiza??o dos dados e uma cultura orientada por eles. Uma governan?a de dados eficaz envolve a clareza das fun??es e responsabilidades de cada equipe, com descri??es de trabalho detalhadas e líderes de projeto como pontos de contato entre TI e negócios. A documenta??o de processos e a padroniza??o de procedimentos garantem que todos saibam o que é esperado deles. A falta de clareza nessas responsabilidades pode levar a lacunas, redundancias e uso inadequado dos dados. Políticas definidas e uma matriz RACI ajudam a comunicar essas responsabilidades de forma clara.

已翻译

赞
Mukundan A P

??Leadership | ????? AI | ?? Data Scientist | ?? Data-Driven Decision | ?? DBMS | ?? GrowthTech | ?? ?? Strategy | ???? Strategic Growth | ??B2B Data-Driven Expert | ?? Speaker | ?? Mentor | ?? Youth Service
举报内容
Clarifying roles in data governance is essential. IT should handle data security ?? and infrastructure, while business units focus on data analysis ?? and strategic decisions. Clear role delineation avoids overlap and confusion, leading to more efficient collaboration. Understanding each group's specific contributions ensures that data management processes run smoothly and effectively.

已翻译

赞

4 Governance Framework

Establishing a robust data governance framework is key to successful collaboration. This framework should outline policies, procedures, and standards for managing data across the organization. It acts as a blueprint that guides both IT and business in their respective roles, ensuring that data is handled consistently and in compliance with regulations. A strong governance framework also helps in setting up accountability mechanisms, which are vital for maintaining the integrity of the data governance process.

添加您的观点

Mukundan A P

??Leadership | ????? AI | ?? Data Scientist | ?? Data-Driven Decision | ?? DBMS | ?? GrowthTech | ?? ?? Strategy | ???? Strategic Growth | ??B2B Data-Driven Expert | ?? Speaker | ?? Mentor | ?? Youth Service
举报内容
A robust data governance framework is vital for collaboration. It should outline policies ??, procedures, and standards for managing data across the organization. This framework acts as a blueprint ???, guiding IT and business roles to ensure consistent data handling and regulatory compliance. It also sets up accountability mechanisms, crucial for maintaining data governance integrity.

已翻译

赞

5 Technology Tools

Leveraging technology tools can greatly facilitate collaboration in data governance. There are various platforms designed to streamline data management processes, allowing for better communication and coordination between IT and business. These tools can automate tasks such as data quality checks, compliance monitoring, and reporting, freeing up time for both groups to focus on more strategic activities. By adopting technology that supports collaborative workflows, IT and business can work more synergistically.

添加您的观点

Mukundan A P

??Leadership | ????? AI | ?? Data Scientist | ?? Data-Driven Decision | ?? DBMS | ?? GrowthTech | ?? ?? Strategy | ???? Strategic Growth | ??B2B Data-Driven Expert | ?? Speaker | ?? Mentor | ?? Youth Service
举报内容
Technology tools are essential for enhancing data governance collaboration. Platforms that streamline data management ??? can improve communication and coordination between IT and business. Tools that automate data quality checks ?, compliance monitoring, and reporting free up time for strategic tasks. Adopting collaborative technology supports synergistic work between IT and business teams.

已翻译

赞

6 Ongoing Training

Finally, investing in ongoing training for both IT and business teams is critical for maintaining an effective data governance collaboration. As data management technologies and best practices evolve, continuous learning ensures that all stakeholders remain knowledgeable and skilled in handling data. Training programs should cover both technical aspects of data governance and the strategic use of data for business decision-making. This not only empowers individuals but also strengthens the overall data governance efforts within the organization.

添加您的观点

Mukundan A P

??Leadership | ????? AI | ?? Data Scientist | ?? Data-Driven Decision | ?? DBMS | ?? GrowthTech | ?? ?? Strategy | ???? Strategic Growth | ??B2B Data-Driven Expert | ?? Speaker | ?? Mentor | ?? Youth Service
举报内容
Investing in ongoing training ?? is critical for effective data governance collaboration. Continuous learning ensures teams stay knowledgeable about evolving technologies and best practices. Training should cover both technical aspects and strategic use of data ??, empowering individuals and strengthening overall data governance efforts within the organization.

已翻译

赞

Data Management

+ 关注

给文章评分

我们借助人工智能创建了此文章。您认为这篇文章怎么样？

很棒不太好

举报此文章

查看全部

Struggling with IT and business collaboration in data governance?

1

2

3

4

5

6

1 Common Barriers

2 Bridging Gaps

3 Role Clarity

4 Governance Framework

5 Technology Tools

6 Ongoing Training

Data Management

给文章评分

感谢您的反馈

更多Data Management相关文章

更多相关阅读内容

Struggling with IT and business collaboration in data governance?

1

2

3

4

5

6

1 Common Barriers

2 Bridging Gaps

3 Role Clarity

4 Governance Framework

5 Technology Tools

6 Ongoing Training

Data Management

给文章评分

感谢您的反馈

查看其他技能