Understand the fundamental aspects of a successful data governance program.
A well-structured data governance framework not only ensures the quality and integrity of data, but also plays a crucial role in compliance, risk management, and strategic decision-making.
Before building, it is important to understand the components of a successful data governance program. The right technology will provide the foundation to support data governance programs, helping companies break down data silos and enabling them to achieve compliance, as well as make better decisions using secured, governed data. Here are five critical components to keep in mind when building a successful data governance program:
Component #1: Data Architecture
According to a Gartner report, data and analytics leaders are quick to highlight the need to break down silos across business areas so that data and analytics can be treated more as an enterprise-wide asset. However, overcoming silo mentality in business areas is one of the most challenging aspects of data and analytics governance. Rigid legacy data architectures promote data isolation by hindering the sharing and dissemination of information throughout the entire organization.
Legacy architectures also make it difficult for companies to organize information coherently. Siloed, disorganized information makes it impossible to apply data governance, whether that be tracing data lineage, cataloging data, or applying a granular security model. Data discovery, data inventory, and tracing data lineage are made easier with a technology platform that provides transparency into the source and granularity of data.
Component #2: Data Quality
Data governance involves oversight of the quality of the data coming into a company as well as its usage throughout the organization. Data stewards need to be able to identify when data is corrupt, inaccurate, or outdated, or when it’s being analyzed out of context. They need to be able to set rules and processes easily. The ability to trust data is a cornerstone for data-driven organizations that make decisions based on information from many different sources. Most organizations believe understanding the quality of source data was one of the most serious bottlenecks in their organization’s data value chain.
Component #3: Data Management
Data governance requires companies to answer an important set of questions:
- What data do I have, and where does it reside?
- Who has access, and how do they use it?
Data management is key to performing this sort of data inventory; a strategy and methods are needed for accessing, integrating, storing, transferring, and preparing data for analytics. Effective data governance grows out of data management maturity, yet almost half of organizations struggle with data management deficiencies.
Component #4: Data Security
Along with the proliferation of data sources both inside and outside enterprises, data breaches are on the rise. Data governance is vital to improving data security. Like successful data management, data security hinges on traceability - knowing where your data comes from, where it currently is, who has access to it, how it’s used, and how to delete it.
Data governance sets rules and procedures, preventing potential leaks of sensitive business information or customer data so data doesn’t get into the wrong hands. However, legacy platforms create siloed information that is difficult to access and trace. Those silos are often exported, sometimes to spreadsheets, and duplicated to combine data with other siloed data, making it even harder to track that data.
Component #5: Data Compliance
Businesses often begin thinking about data governance when they need to comply with regulatory policies such as GDPR, HIPAA, PCI DSS, and the U.S. Sarbanes-Oxley (SOX) law. In a Dataversity report, 48% of companies ranked regulatory compliance as their primary driver for data governance. These regulations require organizations to be able to trace their data from source to retirement, identify who has access to it, and know how and where it is used.
Data governance sets rules and procedures around ownership and accessibility of data. Without it, sensitive information can get into the wrong hands or be improperly expunged, leading to governmental or regulatory financial penalties, lawsuits, and even jail time.
Building Your Data Governance Program
By incorporating these key components into their governance strategy, businesses can establish a solid foundation for data management, ensure data quality and security, and foster a culture of responsible and effective data stewardship.
If you need help building a data governance program that maximizes the value of your data assets, contact Concord. We're here to support your data governance journey and ensure your business thrives in the data-driven landscape.
