Data governance is important because it brings meaning to an organization's data. Adds trust and understanding to an organization's data through management and a robust business glossary, accelerating digital transformation across the enterprise. A data management program is essential for protecting sensitive data and complying with privacy regulations. The right approach can also improve the way people use, analyze and share data across the company, increasing accountability and improving results.
A TDWI study revealed that 36% of data leaders consider data governance to be a key priority for improving the success of an organization with business intelligence (BI) and analytics. Data Governance (DG) is the process of managing the availability, usability, integrity and security of data in business systems, based on internal data rules and policies that also control the use of data. Effective data governance ensures that data is consistent and reliable and that it is not misused. It's increasingly important as organizations face new data privacy regulations and increasingly rely on data analysis to help optimize operations and drive business decision-making.
Everything an organization does must be linked to one of the three drivers of universal values. With the London Interbank Supply Rate (LIBOR) ending at the end of next year, organizations around the world are facing a significant data management challenge. This could complicate data integration efforts or create data integrity problems that would adversely affect the accuracy of business intelligence (BI), business reporting, or analysis applications. Sometimes known more formally as a data governance office, it coordinates the process, conducts meetings and training sessions, tracks metrics, manages internal communications, and performs other administrative tasks. They meet with data owners and enforce data governance policies and procedures, in addition to training new data owners and employees in data governance.
Within the commonly accepted data governance framework, you should establish principles that make sense for your environment. Data security is important, but a data management program can also enable cross-functional decision-making and business analysis. The objectives and results will be unique to each organization once the data security requirements are met. This could cause problems for companies that must comply with the growing number of privacy and data protection laws, such as the European Union's GDPR and the California Consumer Privacy Act (CCPA).
Implementing a robust data governance program ensures the security, standardization, and integrity of data within your organization. When defining data governance, it is important to distinguish between data governance and data management. The better the organization manages the data, the greater the likelihood of obtaining a positive outcome, all things being equal. Implementing the right metadata management solution is critical to obtaining business value as data volumes and the variety of connectors increase.
Companies with strong data governance have an advantage when it comes to transitioning contracts. In addition, high-profile data breaches and laws such as the GDPR and the CCPA have made incorporating privacy protections into data governance policies a central part of governance initiatives. The improved context of metadata allows for data discovery, data quality, analysis of the impact of the data lineage, and the detection of personally identifiable information (PII).
