It goes without saying that an organization’s most important asset is data. Meanwhile, the value of data keeps increasing with the growing trend of data usage and analysis. In today’s world, organizations have access to large volumes of data stored on-site and digitally.
To leverage the power of data for decision-making, business leaders need to ensure the quality and reliability of data. Data governance forms the basis for digital transformation and effective data asset management. Implementing data governance for big data organizations might seem like a daunting task if you don’t understand the concept. To help put it in perspective, we explore the meaning, best practices, and benefits of data governance.
What is data governance?
The answer to the question “what is data governance?” isn’t far-fetched. Data governance encompasses the practices, policies, technologies, and processes needed to manage and protect an organization’s data asset. The system defines the roles and responsibilities for acquisition, data cleaning, storing, gathering, and utilization of data.
Data governance seeks to upgrade poor data quality to meet specific quality data standards. With a data governance framework, business leaders can create policies and workflows for the use of data. In addition, they can monitor data practices and gather helpful feedback.
Also, data governance finds applications in various industries, including financial services, manufacturing, healthcare, and energy. An organization can standardize the collation, storage, and gathering of valuable insight with an efficient data governance system, which users can utilize to make a more thoughtful business decision.
Take, for example, the marketing team of an ecommerce company that uses the insight gained from data governance to create personalized products that suit customers. This will also enhance data privacy and reduce the risk of data breaches.
It’s widespread to find people use data governance and data management interchangeably. Although they share a couple of similarities, the two concepts are not the same. Data governance refers to collecting practices, policies, roles, and processes that guide data management within an organization. In contrast, data management covers the technicalities involved in managing data.
Data governance best practices.
Data governance should be business-driven. Business leaders must lead data governance programs. More so, they must make the decisions on practices, policies, standards, and rules. This will help promote user buy-in and encourage members of the workforce that handle data to agree to business-wide data governance policies.
There’s a need for business users, and data analysts must regularly undergo training to acclimatize themselves with data privacy rules, data usage rules, and data management mandates.
Ensure business-wide data quality and master data management and establish policies for data management in big data environments.
Data processes must comply with legal requirements.
Benefits of data governance
There are many benefits of integrating a data governance system into your business processes. We’ve highlighted a couple of these benefits below.
Break down data siloes: One of the critical objectives of data governance is to dismantle data silos that exist in an organization. These silos stem from disparate data sources without an enterprise data architecture.
Increases employee efficiency and productivity: Data governance helps to standardize data management throughout the organization, which helps prevent duplication of efforts and enhance team collaboration. The entire workforce stands to benefit from the standardized data, which invariably increases productivity. Increased efficiency translates to increased productivity, profitability, and scalability.
Strengthens data security: Data governance is responsible for assigning roles that instill some level of accountability in data managers and staff that access data. It also minimizes the potential of misuse of data, loss of data, and data breach.
Better business decision-making: Data governance gives business leaders access to clean and reliable data to make timely, informed decisions.
Effective data management: Another data governance objective is to ensure effective data management. The framework helps users avoid data errors and misuse of data. With data governance, business leaders can monitor data usage and enforce policies that promote good data management.