The biggest obstacle to establishing a Data Governance posture can be scale. Metaphors about boiling saltwater aside, most organizations on a Data Governance journey will find the most success by starting with smaller use cases and scaling out. We call this Agile Data Governance.
Can Agile Data Governance work for you? Ask yourself these challenger questions to identify Agile Data Governance opportunities in your organization.
As Part One of this series outlines, one of the primary functions of Data Governance is accessibility – or making data available to the right user at the right time.
Identifying common issues and bottlenecks can pinpoint immediate opportunities for accessibility improvements and produce quick wins. These issues could include inconsistent data definitions, data quality problems, lack of data ownership or accountability, or problems with data access and security problems.
To get started, you should audit your existing infrastructure to determine where data is stored. Taking data out of siloes allows you to create domain-specific data marts – promoting usability and supporting domain-specific data products with a governed data federation. Data accessibility initiatives can provide immediate ROI – the cost-savings associated with replacing brittle ETL systems often pay for modernization tools. Eliminating multiple data warehouses also improves security and control functions.
A lack of common understanding of data can lead to inconsistency and misinterpretation. Establishing a business glossary that provides a common language and interpretation of data across the organization is an easy first use case and will introduce Data Governance to stakeholders throughout your organization. While tools exist to automate and manage data dictionaries, the first iterations of your data dictionary can take place in Excel. Most importantly, you will want to document the following:
Maybe you don’t have to reinvent the wheel! The concept of Data Governance has been a hot topic since the early 2010s, thanks to innovations in big data management, increased regulatory pressures, and exponentially growing data volumes. Especially in larger organizations, there might be business lines that have started Data Governance initiatives you can build from. If you have a successful Data Governance initiative underway, even if it is one department, document a use case to expand on their work, learn from their experiences, and apply it to other areas. For example, if your finance department has created its own data catalog, the rest of the organization could immediately benefit.
Regulatory compliance can be one of the biggest drivers of Data Governance initiatives. If you are in a regulatory-intensive industry, such as banking or healthcare, you might want to identify a use case around improving Data Governance to meet compliance requirements. For example, if your organization needs banking regulatory compliance, improving Data Governance could help ensure that all personal data is appropriately identified, secured, and managed. First steps in a Data Governance use case for compliance include:
A Data Governance use case could involve implementing a metadata management solution if current management is poor or non-existent. This will help users understand where data comes from, how it changes over time, and how it is connected to other data.
With metadata management you can:
With a first use case in mind, you will be ready to launch your Agile Data Governance initiative. In our final installment of the four-part series, we will examine tools that promote collaboration and automation throughout the data lifecycle. Or, download your complete Agile Data Governance Guide here.