Data governance for security and data quality
1. Data governance for security and data quality
Data governance enables cloud security teams to ensure data is private, accurate, secure, available, and usable. In this video, we’ll explore how you can use data governance to maintain data quality and keep data secure. Data governance is a set of processes that ensures that data assets are managed throughout an organization. These processes are everything an organization does to ensure data is private, accurate, secure, available, and usable. The processes people follow, the actions they must take, and the technology supporting them throughout the data life cycle are all included in data governance. Data stewards are an important part of data governance. Data stewards are subject matter experts who are responsible for collecting and managing data, and preserving the quality of the data. Data governance can be used to help maintain data quality. Usually, data quality is judged on six dimensions: accuracy, completeness, consistency, timeliness, validity, and uniqueness. Let’s examine each of these dimensions. Data is accurate when it can be confirmed with a verifiable source. For example, an accurate email address for a team member ensures they can be reached. Data is complete when there is enough data to deliver meaningful decisions and inferences. For instance, when completing an online form, some fields may be required while others are not. The data is complete when all the required fields have information. Data is consistent when data stored and used at multiple instances matches the values across various records. Suppose a business has more than one customer database. If a specific customer's name is spelled differently in each database, the data is not consistent. If the name is spelled the same way in each database, the data is consistent. Data timeliness means that the data is available when the user needs it. For example, if an auditor is conducting a review, the audit report data must be ready when the auditor needs to access it. Data is valid when value attributes are aligned with specific requirements. For instance, if a person is purchasing a product online, they need to input their credit card number. The number is valid if the correct number of characters, of a verified credit card number, are in the credit card number field in the payment form. And data is unique when there are minimal overlaps or duplicates. Consider a salon customer who uses an online form to make two appointments for the same service, at the same time, on the same day. If that customer record is duplicated in the system, then the record is not unique. Data quality means your data is complete, accurate, available when you need it, and fits with the organization’s requirements. Having formal governance processes in place to maintain the quality of data will help to ensure that your organization’s data maintains a high quality. For example, say you’re working on a data governance framework. You’ll want to make sure to create processes that address the accuracy of data, and ensure that your data is available when you need it. Establishing clear policies and procedures for data governance helps to protect and secure data. The policies and procedures in your governance plan or framework should cover data access, use, storage, and disposal, and should align with industry standards and regulatory requirements. For example, policies and procedures should prevent threat actors and other unauthorized users from accessing certain confidential data. There must also be policies and procedures in place, so that authorized users are able to gain access to the data. When you collect, keep, and use data in secure, and effective ways, you’re practicing data governance. Data governance can help you and your organization maintain high quality secure data that meets regulation and policy requirements. Now that you know more about how you can use data governance, you can apply those skills to maintain high quality standards and keep your data secure!2. Let's practice!
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