The data governance market is expected to grow by 23% a year between 2020 and 2025. This growth represents a shift in how large organizations collect, use, and analyze data.
As an IT professional, you’re responsible for implementing data governance best practices. You’re the one that ensures data appears consistently across platforms and departments.
Data Governance is crucial to an enterprise’s success. It is imperative that you have a system in place that ensures your data is accurate, secure, and up-to-date. This blog article will cover 10 steps on how to get started with Data Governance.
That’s how you get high data quality so managers can make the most informed decisions possible. The quality of data is even more important as businesses turn to AI and automation.
Automation and AI rely on quality data in order to function well. You also have data compliance issues to deal with as well.
That seems like a lot, but with the right data governance best practices, you’ll be ready to tackle these challenges. Read on to discover the top three data governance best practices to employ in your organization.
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These policies will identify what data is being collected, how it’s being used, who has access to it, and what happens to it when the project or study has ended.
1. Create a Data Governance Framework
At the heart of good data governance is a data governance framework. This defines the who, what, and why behind the data.
You define who is responsible for data. A standard framework assigns data owners, data stewards, and a data governance committee.
Data owners are those who are ultimately responsible for data. Data stewards are employees that handle or have access to data. The committee sets the rules and policies of data governance.
What data do the policies and rules apply to? The committee decides what data needs to be elevated to this level. This usually includes data that is sensitive, such as financial information.
Data that has operational importance or requires compliance also falls under the data governance policies.
The committee also needs to get clear about why the data is so important to the organization. This helps you communicate to employees later on.
2. Set Clear Goals
Create a specific set of goals with an outcome. Clearly defined goals lead to better data governance.
You can set goals to reduce operational costs, maximize the value of data, and minimize risk. The goals should be strategic and specific enough to apply to the operations of the business.
Defining the Data Governance Process: Developing a data governance process is the first step in managing your data, which can help reduce risk by ensuring information is handled with care. Here are four key steps to manage your data: identify the stakeholders, develop the policy, establish the framework, and provide training.
3. Training Employees
The most difficult part of data governance is employee buy-in. Training data owners and data stewards are a necessary part of data governance.
One of the key data governance best practices is to explain to companies why data governance exists at your organization. You should then have a training program for data owners and data stewards.
These trainings should occur regularly, which goes a long way to create a collaborative data governance culture.
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Defining Data Governance
Data governance can be defined as the process of making sure that data is used in the best possible way, the most appropriate way for achieving an organization’s goals. So how do you get started with data governance? The first thing to do is to define your data governance policies. What are your standards? What are your guidelines? These are all things that need to be discussed and documented so they can be followed by everyone in the company.
Importance of Data Governance
Data is the foundation of success for any organization. This includes things like setting standards, establishing guidelines for data use and storage, and identifying data sources.
Data Governance is the set of principles that guide an organization to manage its data well. Think of it as being for the benefit of both the organization and its customers. Here are 10 steps to help you achieve Data Governance success:
Enforcing Policies and Procedures for Data Privacy
The first time I came across the term “data privacy” was when I read about Facebook’s Cambridge Analytica scandal. This is one reason why companies need to have guidelines for what’s acceptable and what’s not.
Thinking Ahead to Implementing Compliance with GDPR
In May 2018, the EU will enforce the General Data Protection Regulation (GDPR), which is a set of wide-ranging new data privacy laws designed to protect the personal data of EU citizens. GDPR requires any organization that has access to or uses European Union residents’ data to implement a data protection program with clear instructions and processes for how they collect, store, and use that information.
Creating a Sensible Set of Rules for Sharing Data
The first step to creating a sensible set of rules is defining what it means for data to be sensitive. Sensitive data can be defined as any information that could lead to harm if not protected. For example, credit card numbers or social security numbers are examples of sensitive data.
Execute These Data Governance Best Practices
Data governance is a necessity because your organization relies on data to make decisions and improve productivity. Data governance sets the policies and procedures to organize data and ensure accuracy.
These data governance best practices introduce you to a data governance framework. You’ll set your goals and get employee buy-in so everyone in your organization becomes a good data steward.
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