Master the MDS balancing act: Data governance vs. Self-serve
A guide to finding the happy balance between enough governance to tame data chaos and enough self-service to empower stakeholders.
A guide to finding the happy balance between enough governance to tame data chaos and enough self-service to empower stakeholders.
Effective data governance builds a culture of trust and collaboration around data.
Data governance frameworks play a critical role in helping organizations use their data assets to their fullest potential. They provide direction and structure for how an organization can collect, store, and utilize data while ensuring compliance with laws and regulations.
Data governance and management is a term that has become more commonplace in recent years. However, many organizations are still struggling with how to implement effective data governance and management strategies. This lack of focus is becoming more and more apparent as the importance of data management continues to grow. Here are the four key pillars that will help you successfully implement your data governance strategy.
Data governance is the process of managing and protecting data throughout its lifecycle. It involves establishing policies, procedures, and standards for how data is collected, stored, used, and shared. This requires systems that are complex to be put in place by several stakeholders across the organization. Many organizations look at selecting the right software to implement a framework.
A good data governance strategy should benefit all users of your organization’s data—not just those with technical responsibility for it. Recent years have seen the increasing importance of data as a strategic asset, as several companies have used it to unlock and create value. Increasingly, companies are turning to data governance programs as a foundational pillar of their data strategy (like data mesh) to improve their data sets’ quality, consistency, usability, and security.
Five things you need to know about data governance tools: Data governance refers to the methodologies, procedures, and standards that control how your organization processes, manages, stores, and shares data. Legislation in your jurisdiction or industry — such as General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), and Health Insurance Portability and Accountability Act (HIPAA) — might require you to safeguard all the data that flows through your enterprise.
According to IDCs Global Datasphere, 64.2 ZB of data was created in 2020 alone. This number is projected to grow by 23% annually from 2020-2025. Therefore, we need data governance frameworks for efficient data management and control. This will help us extract maximum value out of such high volumes of data. Such frameworks would be required for data integrity, data protection, and data security. Indeed, according to BDO, the average data breach cost has been estimated to be around USD 3.8 million.
Effective control and governance over your data assets is vital for long-term business success. By keeping your data available, reliable and usable for analysis, consumption and sharing, you can ensure data quality, data security and data reliability is consistently met. However, many organizations today struggle to implement governance frameworks over their data, which has once again highlighted the importance of data governance. So, what is data governance?
Many organizations are still under the impression that data governance can be achieved by implementing a data governance tool. This is false.