Data governance is an overarching strategy for organizations to ensure the data they use is clean, accurate, usable, and secure. With the increasing volume and complexity of data, it has become more critical than ever for businesses to have a systematic approach to managing their data assets.
Data governance involves the creation of standards and procedures for acquiring, managing, and processing data. It also includes policies for ensuring the security and privacy of data, as well as guidelines for data retention and disposal. Ultimately, the goal of data governance is to ensure that data is consistent, reliable, and accessible to those who need it.
Data governance is a complex process that involves multiple stakeholders from different departments. Business units, IT, and the compliance department all have a role to play in data governance. Some organizations even appoint a Data Governance Officer to oversee the process and ensure that all stakeholders are working together effectively.
The first reason why data governance is essential is to ensure data availability. Even the most sophisticated business intelligence (BI) systems are of no use if users cannot find the data they need to power them. Self-service BI has made it even more critical to ensure that data is easy to locate and use. Data governance involves setting up standards and processes for acquiring and handling data, as well as ensuring that those processes are being followed.
The second reason is to ensure that users are working with consistent data. When different departments work from different sets of data and reach different conclusions about the same subjects, it can lead to confusion and poor decision-making. By ensuring that data is consistent across the organization, data governance can reduce arguments at the executive level, increase confidence in decision-making, and improve overall enterprise performance.
The third reason is determining which data to keep and which to delete. Data hoarding can lead to IT servers and storage units filled with useless junk, making it hard to locate any data of value. It can also lead to users using stale or irrelevant data for important business decisions, increasing vulnerability to data breaches and increasing IT expenses. Good data governance involves carefully considering which data is important to the organization and which should be destroyed. It also includes procedures for systematic data retirement, archiving, or destruction according to age or other pertinent criteria.
The fourth reason is to resolve analysis and reporting issues. Consistency across an organization’s metrics and the data driving them is critical to successful business analytics. Without clearly recorded standards for metrics, people may use the same word, yet mean different things. Self-service analytics or business intelligence can be a boon to an enterprise, but only if people interpret metrics and reports in a consistent way. Data governance involves establishing standards for metrics and ensuring that they are being applied consistently across the organization.
Finally, data governance is essential for compliance purposes. Many industries are subject to strict regulatory requirements for data privacy and security. Data governance can help organizations meet these requirements by establishing policies and procedures for data security and privacy. It can also help ensure that data is accurate and reliable, which is critical for compliance reporting.
In conclusion, data governance is essential for organizations to ensure that their data is clean, accurate, usable, and secure. By establishing standards and procedures for acquiring, managing, and processing data, organizations can improve data availability, consistency, and compliance while reducing costs and increasing efficiency. Data governance is a complex process that requires the involvement of multiple stakeholders from different departments, but the benefits are well worth the effort.