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The need for Secure, Compliant, and Trustworthy Data
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 organisation.
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.
Data concerns continue to grow with the emergence of new technology. As we look beyond 2023, there are several data governance concerns that organizations should be aware of and take steps to address.
Enhanced Data Security
Data Quality
Data Privacy
Data Analytics
In an era where cybercriminals are becoming increasingly sophisticated, organizations must implement robust safeguards to protect their data. This includes stringent access controls, encryption, and other security measures. Both on-premises and cloud computing environments pose risks if not adequately managed.
As data collection expands, ensuring the accuracy and currency of data is paramount. Organizations must establish processes to regularly verify data accuracy and address discrepancies. Monitoring data duplication and replication practices is essential to prevent data sprawl and associated risks.
Compliance with data privacy regulations such as GDPR, CCPA, and CPRA is crucial. Organizations must implement processes to securely collect, store, and use customer data. Adequate measures should be in place to protect customer data privacy and facilitate prompt deletion upon request.
Effective and responsible use of collected data is essential. Organizations must ensure compliance with data privacy regulations when utilizing analytics. Ethical use of data, especially with machine learning or AI, is critical. Managing report and dashboard creation to avoid duplication is also important.
Effective data governance is at the heart of managing the data used in operational systems and the business intelligence and analytics applications fed by data warehouses, data marts and data lakes. It's also a particularly important component of digital transformation initiatives, and it can aid in other corporate processes, such as risk management, business process management, and mergers and acquisitions.
A successful data governance program requires constant monitoring, updating, measurement, collaboration, and education. Still, when implemented effectively, it can add tremendous value to organizations that are on the journey to becoming increasingly data-driven.