Modern businesses generate more data than ever before from multiple sources, and with the rise of the cloud, businesses have several options at their disposal to leverage that data for competitive advantage. This interest in utilizing data to make strategic business decisions is what drives many organizations to form a data governance framework: a set of defined principles and processes to define how data is collected, stored and used within an organization.
However, many organizations quickly learn that simply defining a data governance framework is insufficient to hitting business goals. It’s vital to then take the next step of implementing the right data governance software to enable execution of your framework.
DEFINITION
A data governance tool is a software solution built to help organizations manage, control, and ensure the quality, security, and compliance on the entire lifecycle of data, from creation to curation to archival and deletion. Data governance platforms provide technologies and processes to help organizations establish and enforce policy-based principles to ensure data is accurate, trustworthy and secure. Data governance tools enable data stakeholders on both the business and technical sides to coordinate procedures and processes.
Every organization is at some stage of maturity with respect to its ability to manage data effectively. Use of a data governance tool can help drive increasingly sophisticated levels of data governance.
Selecting an appropriate data governance tool is mission critical to maintaining an effective data governance program. Here are a few important questions to ask during the selection process.
Modern data governance software must go beyond compliance, supporting your desired business outcomes.
As your business grows, so will your volume of data, so make sure it can handle both your current data requirements and future projected growth.
A proper data governance tool should accommodate your data infrastructure, not the other way around.
Data quality is a cornerstone of data governance, so make sure it will maintain high data quality by way of automated checks and monitoring.
Automation can greatly streamline enforcement of governance policies, and AI and machine learning can facilitate data discovery and quality management.