Data Governance is the management of data and processes to ensure data can be used consistently, securely, and following policies and other standards. This is how enterprise-grade data management works:
- Disconnects departmental silos
- Determines policies
- This supports the data stewardship process
- It shows how data are organized
- Align terms within the organization
- It connects technical databases with terms.
Data governance is crucial because it goes beyond data administration or master data management. It allows data citizens to access the correct information and extract value out of the data.
What are the advantages of data governance?
Data governance is a valuable tool for all employees. Data governance can be used to address many different use cases. However, data governance adds value in the same way.
Data Governance Training plays an important role in regulatory compliance. This ensures that organizations meet all regulatory requirements. This is essential for minimizing risk and reducing operational expenses.
Data governance creates a common language
Data governance allows team members from across departments to share business terminology, KPIs, and rules. This ensures that everyone within an organization understands the same language. This shared language allows organizations to have a common understanding of the business and make use of consistent, trustworthy information.
Data governance brings people closer together to collaborate
Data governance allows for collaboration by using a common language. Co-workers within and outside departments can communicate using the same terminology and analyze the identical data. Clarifying roles and responsibilities helps eliminate confusion and facilitates data collaboration and data processing.
Data governance makes data meaningful
Data governance gives context to an organization’s data. It allows teams to organize, document, evaluate and assess the quality of information assets. Data governance ensures that all colleagues have the right context to access and trust data. It also establishes controls and identifies responsibilities.
Create a plan for data governance
Now that we understand the importance of data governance, let’s talk about putting data governance into practice. Consider the following steps as you develop your data governance strategy:
1. Acknowledge the gap between IT and business
IT may be able to support your data as custodians but it is the business that knows the data best and can explain how P&L results and supply chain results drive real business results.
Your IT department should be empowering users to use technology platforms. They should also enable self-service. Employees who support IT tools should be able to access the vast amount of data that successful organizations use every day.
The ability to define and create their terms and data flows within a system of records will allow the business lines to achieve greater efficiency and solve business problems quicker.
2. Discuss the value of data governance with business users
If business users still view data governance only as an IT issue, explain the value high-quality data can bring to every unit of the company. Communicate the ROI and estimate the benefits of a data management program to make them feel more connected. Discuss the benefits that different teams have.
Sales and Marketing – Increase sales through the use of higher quality data to create more targeted campaigns
Procurement – Lower costs by using governed Data to optimize purchasing processes, supply chain, and procurement
Legal and compliance: Avoid violations, non-compliance, and fines. Establish ownership and policies around data.
Finance – Improve reporting by providing better governed easily accessible data.
3. Technology should be used strategically
Many technologies have the potential to identify data and create tag terms that will accelerate data recognition. But, the business owners and stewards must verify the bottom-up approach. Unique business processes can often be exceptions, which mean that they require human interaction. If a growing company wants to improve its profits and decrease its risk, it will often outperform the automated environments.
