You're drowning in data growth at work. How do you decide what to keep for the long haul?

Reduce data collection to only what is necessary for business operations and regulatory compliance. Minimize storing sensitive information unless absolutely required!

Agree with the spirit of the current statement however I would change the language somewhat to ensure that this is an ongoing effort. "Data Audit" would be better described as "Data Awareness" as audit tends to be a one off or scheduled effort in some organisations. As an organisations catalogue of data may be subject to swift change the start of the paragraph should be "Maintain comprehensive data awareness. This means being actively aware of all the data..."

I agree with most comments and add, consider the value of improvement and modeling the effectiveness of current business practices through the analysis of historical data. Before you delete consider repurpose. Consider the insights historical data may provide to your current challenges.

Implement a robust data governance framework that defines clear policies, processes, and responsibilities for data management, including data retention and archiving. Collaborate with stakeholders to identify the data that is critical for supporting key business functions, decision-making, and regulatory compliance. Focus on retaining high-value data. Develop a data lifecycle management strategy that includes guidelines for data retention, archiving, and disposal based on the data's importance, sensitivity, and regulatory requirements. Use automated data tiering solutions to move less frequently accessed data to more cost-effective storage, while keeping frequently used data on high-performance storage.

Governança de dados tem sido a base para o sucesso de projetos de TI incluindo os mais em moda como os de IA. Mas ainda é uma questão sensível nas empresas já que é muito comum problemas como coleta, validação, padronização e manutenção de dados o que acaba por impactar em uma cadeia importante envolvendo além de governança, custos e vulnerabilidades da mais variáveis e indesejáveis.

Develop tailored training programs that educate employees on data privacy best practices, cybersecurity threats, and compliance requirements. Foster a culture of data security awareness across all levels of your organization.

En mi caso particular, ha sido de suma importancia tener en consideración lo que dicta la ley en cuanto a la regulación de cada tipo de dato que se almacena. Se deben establecer políticas que abarquen todos y cada uno de los datos y documentos que genera la compañía, teniendo también presente los procesos que pueden estar utilizando datos históricos. Utilizar distintos tipos de almacenamiento es una estrategia a considerar al momento de abaratar costos.

2 important factors to consider in drafting a retention policy are Regulatory requirements and the business. Retention policy must accommodate prevailing regulations and it must also align with the business flow, giving room for analytics and business opportunities with data exploration. Implementing a retention policy ensures data is retained if and only if it is necessary or beneficial to the business.

Establish clear policies and procedures for managing data from creation to deletion. This includes defining retention periods, archival processes, and secure deletion methods.

With data growing rapidly, a data manager faced tough decisions. * They implemented a data lifecycle management policy, categorizing data by relevance and frequency of access. * Critical and frequently used data was stored on high-speed storage, while less relevant data was archived. * They collaborated with stakeholders to identify key data sets essential for long-term business goals. By regularly reviewing and purging obsolete data, they maintained a lean, efficient database, ensuring only the most valuable data was kept for the long haul, balancing growth with strategic needs.