Over the past ten years, the sophisticated use of data to improve business decision-making and offer increased customer value has forever changed the business landscape. Data visualization to analytics to AI requires continual evaluation and improvement of data use cases. But with all the hype and change in areas of data modernization, data governance has seen minimal improvement until now.
Data governance is a collection of processes established by enterprises to manage the data's availability, usability, and overall integrity. Data governance is critically important for organizations that are becoming increasingly data-driven. Data governance ensures that the data is trustworthy and adheres to the data standards and policies implemented by the organization.
As new technologies continue to emerge, data volume will grow exponentially. Therefore, organizations must ensure proper controls to prevent misuse and protect their data. If employees, customers, partners, the public, and regulators don’t trust an organization’s data, the credibility and value of the organization is minimized. Furthermore, an unstructured data governance program can result in data silos, high data management costs from duplication of efforts as well as the absence of a single source of truth.
With cybercriminals' increasing sophistication and prevalence, organizations must ensure adequate safeguards to protect their data. This includes having proper access controls, encryption, and other security measures. Organizations must also know the risks associated with on-premises and cloud computing environments. Both data storage solutions can leave them vulnerable to attack if not adequately controlled.
As data collection grows, organizations must ensure that the data they collect and use is accurate and current. This means having proper processes to ensure that data is regularly checked for accuracy and that any discrepancies are rectified. Data duplication and replication practices must also be monitored to ensure data sprawl does not increase risks.
Organizations must comply with data privacy regulations such as the General Data Protection Regulation (GDPR, CCPA, and most recently CPRA). This includes having proper processes in place to ensure that customer data is collected, stored, and used securely and competently. Organizations must also ensure that they have adequate measures to protect the privacy of their customer’s data and the ability to delete it when requested quickly.
Organizations must ensure that they have proper processes in place to ensure that the data they are collecting is used effectively and responsibly. Organizations must also ensure that any analytics use complies with data privacy regulations. When introducing machine learning or AI, ensuring that data is used ethically is critical. Finally, new reports and dashboard creation should be managed to limit duplication that can reduce quality.
Storm Reply’s Governance and Strategy Practice delivers value to its clients by fully understanding the complexities of Data Governance programs and how they evolve as the business climate and technology evolve. The firm has built solutions to help many of the world’s largest organizations deliver a risk-reducing solution for data governance that drives value and reduces costs. For more information contact email@example.com