Given the rise of services as application software (SaaS) and cloud-based apps where employees, suppliers, and customers all generate, store, access, utilize, or consume data constantly, data governance is a more critical initiative than ever. Without oversight and accountability, the wrong data could be generated and the right data could be lost, severely disrupting business operations.
What Is Data Governance?
A robust, built-out data governance program defines who within an organization has the authority and control over data assets and how they may be used. It encompasses the people, processes, and technologies required to manage and protect data.
Benefits of Data Governance
The goals of a data governance program are to establish the processes that employees and managers alike can follow in order to standardize, integrate and protect corporate data. These goals provide innumerable benefits, including the following:
- Minimize risks
- Establish internal and external rules for data use
- Remain compliant with industry standards and government regulations
- Increase the value of data
- Reduce costs
- Improve efficiency and speed
- Increase productivity and customer satisfaction
Data governance is just one part of the overall discipline of data management. Whereas data governance is about the roles, responsibilities and processes for ensuring accountability for and ownership of data assets, data management deals with the processes, “used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control and purge data” according to DAMA.
While data governance takes a higher-level view of the accountability related to data, data management deals with how that data is collected and used in order to maintain the organization’s operations. Data management would address data inconsistencies found across different systems. A common error is the use of multiple CRM instances across different divisions within a company. Names in one database might be listed, tagged or grouped differently than in another database. This can complicate data integration efforts and create data integrity issues that affect the accuracy of business intelligence, reporting and analytics. Fixing this would require strong data management that is informed by the higher-level data governance policies in place.
What a Data Governance Framework Looks Like
Data governance includes several components beyond simply storage and security. Data is also more than just numbers; documents, files and entire applications can be considered data. As such, there are several components that need to be considered as part of a data governance framework, such as the following.
- Data architecture: The overall structure of data and data-related resources as they relate to enterprise architecture.
- Data modeling and design: Analysis, design, building, testing and maintenance.
- Data storage and operations: Physical or cloud-based storage and management.
- Data security: Privacy, confidentiality and access management.
- Data integration and interoperability: Acquisition, extraction, transformation, movement, delivery, replication, federation, virtualization and operational support.
- Documents and content: Storing, protecting, indexing and enabling access to data found in unstructured sources and making this data available for integration and interoperability with structured data.
- Reference and master data: Managing shared data to reduce redundancy, ensuring better data quality through standardized definition and use of data values.
- Data warehousing and business intelligence: Managing analytical data processing and enabling access to decision support data for reporting and analysis.
- Metadata: Collecting, categorizing, maintaining, integrating, controlling, managing and delivering metadata.
- Data quality: Improving quality by defining, monitoring and ensuring data integrity.
Due to the potential complexity of the types of data under evaluation during a transaction, companies need more than a simple cloud storage and sharing application. Instead, companies should consider a virtual data room (VDR) that has the needs of stakeholders in mind.
Solutions from CapLinked can help companies and their outside advisors, including bankers, lawyers, accountants, and consultants, maintain their data governance program with the strictest of integrity and security in mind.
How To Implement a Data Governance Program
The following steps would be taken to develop and implement a data governance program:
- Select the organization’s data stakeholders. These would be the project leaders and decision-makers.
- Define goals and understand benefits. Goals can be both short-term and long-term, and must be measurable. A measurable goal might be a reduction in mistakes, the speed at which important data is accessed, or customer satisfaction because of a faster mobile app.
- Analyze the current state. It’s important to understand what the strengths and weaknesses of current data collection and management methods might be.
- Develop a roadmap. Like the goals, this can be both short-term and long-term.
- Convince stakeholders and develop a budget. This might include garnering buy-in from senior management, especially if additional resources and tools are needed to measure data governance efforts.
- Implement the data governance program. Create a launch plan, including educational and training materials.
- Monitor and control. This can be ongoing, with reports generated at specific intervals or when milestones are reached.
Data Governance and Virtual Data Rooms: The Perfect Match
When undergoing the due diligence process for an M&A or private equity transaction, it’s not just legal documents that are under review. A thorough analysis of sensitive data covering the target company’s financial and operational performance is critical for thorough due diligence.
To prevent sensitive data from misuse or compromise, a trusted third-party virtual data room (VDR) that contains all the appropriate document hosting and sharing features for the transaction is a must. It delivers confidence to all parties that the strongest security measures are in place, and the tools included will help expedite the entire process, making the content and data flow more smoothly and lopping weeks, if not months, off the entire transaction timeline.
Jake Wengroff writes about technology and financial services. A former technology reporter for CBS Radio, he covers such topics as security, mobility, e-commerce and the Internet of Things.
The Data Governance Institute – Defining Data Governance