Today, many organizations have numerous applications and systems in which data, spanning multiple departments, quickly becomes fragmented, duplicated, and even outdated.
A well-known issue with legacy data platforms is what’s known as the garbage in, garbage out (GIGO) obstacle. As data began to flourish due to cheap storage options and increased digitization, data quality issues and fragmentation proliferated, creating GIGO issues that affected an organization’s business intelligence.
To progress to a future state of mature Data Governance and analytical capability, decision-makers should focus on starting with the integration of the data across an entire enterprise. A Data Governance program will be critical to support the continued growth of an organization.
Data is at the center of People, Process, and Technology, representing a crucial asset used by all three. Simply put, people should embed data in any project to ensure that organizations follow a defined road map around enterprise data governance; technology can also help enhance and automate several processes and transactions.
Data governance is a challenging topic and directly affects how an organization interacts with its data. Successfully applying a Data Governance strategy requires managing the dynamics of an organization that allows for organizational change.