- share with the team best practices and cases of success - provide training sessions with experts - demonstrate the value delivered to the company by other's Data Governance strategies - share articles that explore the need of data governance practices

Data governance might seem like just another box to check. Strong data governance ensures data accuracy, security, and compliance, which are crucial for making informed decisions and avoiding costly mistakes. It’s not just about managing data; it’s about protecting our business and driving success.

To effectively address skepticism about data governance, it's essential to highlight its tangible benefits. Share real-world examples of companies that have significantly improved their bottom line through effective data governance practices. Additionally, present case studies of organizations that suffered significant losses due to data breaches, non-compliance penalties, or poor decision-making based on faulty data. To foster a deeper appreciation for data governance, conduct ongoing training sessions that educate team members about its importance, principles, and benefits for both individuals and the organization. Encourage team members to become data literate and understand how data can be used to drive informed decision-making.

Alguns passos: - Liderar por exemplo - definir objetivos claros e sempre alinhados com o negócio - apresentar resultados tangíveis, mensuráveis - buscar e apresentar ganhos rápidos - feedbacks constantes Neste contexto a comunicação é fundamental.

While implementing data governance is not rocket science, it is also not a simple exercise. There is a lot of confusion around the what, why, and how of data governance, and as a result, a lot of challenges arise in the implementation of data governance. Data governance involves a significant amount of effort, time, investment, and cultural changes that must be taken into consideration to achieve and sustain its success. There are several use cases of data governance, including compliance, improving customer satisfaction, better decision making, data security, data privacy, data analytics, improving operational efficiency, revenue growth, mergers and acquisitions (M&A), partnering and outsourcing, and improving data quality.