Data governance , which is the process of managing availability, usability and security of enterprise systems’ data , is based upon internal data standards and policies that control data usage. Effective data governance ensures data integrity and trustworthiness and prevents data misuse. As organizations are subject to new data privacy regulations, it is increasingly important that they rely on data analytics to optimize their operations and make business decisions.
Inconsistencies between systems in an organization’s data management system may not be fixed if they aren’t properly managed. Customer names could be listed differently in the sales, logistics, or customer service systems. This could make data integration more difficult and cause data integrity problems that can impact the accuracy of analytics, enterprise reporting, and business intelligence . Additionally, data errors could not be identified or fixed, which could further affect BI accuracy and analytics accuracy.
Data governance goals and benefits
The goal of data governance in breaking down silos is a key objective. These silos often form when business units have their own transaction processing systems and lack centralized coordination. Data governance training seeks to harmonize these data systems by a collaborative process with stakeholders from different business units.
Another goal in data governance is to make sure data is used correctly. This is done to avoid data errors and prevent misuse of customer personal data and other sensitive information. It is possible to establish uniform policies regarding data usage, as well as procedures for monitoring and enforcing the policies. Data governance training can also help strike a balance between data collecting practices and privacy mandates .
Data governance can provide many benefits beyond better analytics and regulatory compliance. It also provides improved data quality, lower management costs, and greater access to data for data scientists, analysts, and business users. Data governance can ultimately improve business decision making by providing better information to executives. This should lead to increased revenues and profits as well as competitive advantages.
Who are you responsible for data governance
Data governance is a process that involves many people in most companies. Business executives, IT staff, and data management professionals are all involved in data governance. End users also need to be familiar with data domains that exist within the organization’s systems. These are the primary stakeholders and have primary governance responsibilities.
Chief data officer
If one exists, the chief information officer , is usually the executive in charge of a data governance plan and is responsible for its success. The CDO’s role is to secure approval, funding, staffing, and play a leadership role in setting up the program and monitoring its progress. He also acts as an advocate for it. If the organization does not have a CDO, an executive sponsor will usually serve the same function and act as an executive sponsor.
Data Governance Manager and Team
In some cases, the CDO (or an equivalent executive) may also be the hands on data governance manager. Some organizations designate a data governance leader or manager to oversee the program. The program manager is usually responsible for leading a team of data governance experts who are dedicated to the program. The data governance office is more commonly known as the program manager. It coordinates the process and leads training sessions. It also tracks metrics and manages internal communications.
Data Governance Committee
Although the governance committee is responsible for making policy and standards decisions, it rarely makes them. The data governance committee, or council, is responsible for making policy and standards decisions. It is composed primarily of business executives as well as other data owners. The fundamental data governance strategy is approved by this committee. It also approves associated policies and rules, including those regarding data access and usage. They also determine the procedure for implementing them. It also resolves disagreements, such as between business units about data formats or definitions.
