Azure Data Governance Framework for a Secure Data Environment

A secure data environment is crucial for any organization, and Azure Data Governance provides a robust framework to achieve this. Azure Data Governance is designed to help you manage data risks and compliance requirements.

To establish a secure data environment, you need to define data access controls. This can be achieved through Azure Active Directory (Azure AD), which enables you to manage user identities and access permissions.

Data classification is another critical aspect of Azure Data Governance. By classifying data as sensitive, confidential, or public, you can apply the necessary access controls and retention policies.

Azure Data Governance is a business-friendly approach that helps you manage your multi-cloud data estates. It's designed to support different functions across your business with clear role definitions.

The governance experience includes roles like governance administrators, business domain creators, data health owners, and data health readers. These roles help you define and assign responsibilities within your organization.

Within Data Management, you can easily define and assign business-friendly terminology, such as Finance and Claims. This terminology follows the data governance experience through Data Products and Business Domains.

Data Products are a collection of data assets used for a business function, and Business Domains represent ownership of these Data Products. This structure helps you organize and manage your data in a way that makes sense for your business.

Data governance with Azure also includes Data Quality, which is an assessment of the quality of your data. You can use this feature to identify and address any issues with your data.

Azure data governance offers a centralized way for administrators to manage governance controls across Azure subscriptions with Azure Management Groups. This allows for streamlined management and compliance across your entire Azure environment.

Azure Policy provides a real-time compliance dashboard to enforce, evaluate, and audit policies for all of your Azure services. This ensures that your data is always in compliance with your organization's policies.

Here are some of the key Azure data governance features and services:

A framework is a structured outline of your organization's rules, processes, and role delegations surrounding enterprise data. It's the backbone of your data governance approach.

A solid framework is comprised of several key components, including data governance policy, data stewardship, data classification, data access and control, data privacy and security, data quality management, data retention and disposal, and compliance. These components work together to ensure your data drives success.

A data governance policy is a crucial part of a framework, defining the specific approach to data governance within your organization. It ensures every byte of data is accurate, secure, and accessible in real time.

Here's a breakdown of the components that make up a comprehensive framework:

Azure offers a range of features and services to help you manage your data assets. These include Azure Management Groups, which provide a centralized way for administrators to manage governance controls across Azure subscriptions.

Azure Policy offers a real-time compliance dashboard to enforce, evaluate, and audit policies for all of your Azure services. This helps ensure that your data is compliant with regulations and standards.

Azure Blueprints (in preview) allows you to create, deploy, and update compliant environments with scalable templates. This streamlines the process of setting up and managing your data governance.

Here are some of the key Azure data governance features and services:

A data governance policy defines the specific approach to data governance within your organization, ensuring every byte in your data landscape is accurate, secure, and accessible to those who need it—in real time.

Azure Policy lets you create, assign, and manage Azure policies, helping you enforce compliance according to the standards and regulations your business adheres to.

Policies vary depending on the type of data in question, such as master data, metadata, transactional data, etc.

The following are the stages of data governance:

Implementing data retention policies is crucial, and services like Azure Policy can help enforce them, ensuring data is securely deleted when no longer required.

Data governance and data management are two closely related yet distinct concepts. Data governance refers to the policies, processes, and standards for using data within an organization, while data management focuses on the technical tasks involved in maintaining and using that data.

To implement identity and access management, you can use tools like Azure AD to manage access to data and enforce role-based access control. This ensures that only authorized personnel can access sensitive data.

Azure offers a range of data governance platform services to help organizations manage their data assets, including Azure Policy, which lets you create, assign, and manage Azure policies to enforce compliance with business standards and regulations.

Deploying Atlan for Microsoft SQL Server is a straightforward process that requires a few key steps. First, you need to create a username and password to fetch metadata from Microsoft SQL Server.

To do this, you'll need to grant permissions to the databases you want to crawl, preview, and query in Microsoft SQL Server. This will allow Atlan to access the necessary information.

Once you've granted permissions, you'll need to add permissions to view lineage. This is an important step, as it will enable Atlan to provide a complete picture of your data.

Now that you've completed these steps, you can add Microsoft SQL Server as your source and create new workflows. Simply provide the credentials you've configured to let Atlan fetch metadata.

Finally, run the crawler and schedule it to run hourly, daily, weekly, or monthly. This will ensure that your data is up-to-date and that Atlan can continue to map databases, schemas, tables, views, columns, and routines from Microsoft SQL Server.

Here's a summary of the steps to follow:

Implementing Identity and Access Management (IAM) is a crucial step in securing your data and workflows. Use tools like Azure AD to manage access to data and enforce role-based access control.

Azure AD provides a robust platform for managing identities and access. This includes features such as multi-factor authentication, conditional access, and identity protection. By leveraging these features, you can ensure that only authorized users have access to sensitive data and resources.

To implement IAM effectively, consider the following best practices:

By following these guidelines, you can establish a robust IAM framework that protects your data and workflows from unauthorized access.

Implementing retention policies is a crucial step in managing your data assets. You can leverage services like Azure Policy to enforce data retention policies.

Azure Policy lets you create, assign, and manage Azure policies, helping you enforce compliance according to the standards and regulations your business adheres to.

To implement retention policies, you should consider the level of data governance your organization has achieved. According to the data governance maturity model, a fully governed organization has policies and rules to govern data retention consolidated in the data catalog using classification schemes and enforced everywhere.

Here are the key stages of data governance maturity related to data retention:

By implementing retention policies, you can ensure that your organization is responsible and compliant with data regulations.

Automating processes can make a huge difference in the efficiency of your work. By automating data management processes, you can free up more time for strategic decision-making.

Using Azure Data Factory and other tools, you can automate data ingestion, transformation, and movement. This can help streamline your operations and reduce errors.

Implementing multi-cloud governance is a crucial step in managing your data estate.

The new governance experience is designed with the business in mind, supporting different functions across the business with clear role definitions.

This includes governance administrators, business domain creators, data health owners, and data health readers.

Business-friendly language is used throughout the data governance experience, making it easier to understand and manage your data.

Data Products, a collection of data assets used for a business function, can be easily defined and assigned using business-friendly terminology.

For example, you can use terms like Finance and Claims to categorize your data.

Business Domains, which represent ownership of Data Products, are also defined using business-friendly language.

Data Quality, which assesses the quality of your data, can be evaluated using the same terminology.

Data Access, Actions, and Data Estate Health reports and insights are all accessible through the data governance experience.

This allows you to scan and search data across your data estate assets with ease.

Information Protection is a top priority for any organization looking to safeguard their sensitive data. Azure Information Protection (AIP) is a powerful solution that lets you classify, label, and protect sensitive information based on custom protection rules.

Having a robust data governance practice in place is crucial to protecting your data. This requires becoming a data governance company, which involves adopting a culture of data governance and protection.

Azure Active Directory (AD) provides a centralized identity and access management solution, which helps secure all of your data assets, both on-prem and in the cloud. This includes providing role-based access control.

A well-implemented data governance practice must be simple, efficient, customizable, and flexible to meet the unique needs of your organization. This requires C-Suite alignment and support to activate your unique practice.

Azure AD also provides support for data discovery, which is essential for identifying and protecting sensitive data. By leveraging AIP and AD, you can create a robust defense against data breaches and ensure the integrity of your data assets.

To maximize the value of Azure's data governance tools, follow these best practices. There are nine key best practices to consider, as outlined in a comprehensive guide.

Effective data governance is essential for organizations, ensuring the security, privacy, quality, and compliance of their enterprise data. This is where Microsoft Azure's data governance tools come in, offering a comprehensive set of features and tools to help businesses achieve their objectives.

Atmosera, with nearly three decades of industry experience, can help organizations optimize their data and data governance software. They've helped countless organizations achieve their data governance objectives, making them a valuable resource for those looking to implement a custom strategy.

Microsoft Purview data governance experience is designed to help any organization of any size accelerate business value creation in the era of AI.

Best Practices are essential for maximizing the value of data governance tools. Azure Data Governance Best Practices can be applied to various industries and organizations.

Having nine key best practices can help you get started. Let's look at some of these best practices to see how they can be applied.

Data governance tools can be maximized by implementing data classification and categorization. This helps ensure that sensitive data is properly secured and protected.

Data quality is crucial for making informed decisions. Regularly monitoring and maintaining data quality can help prevent errors and inconsistencies.

Implementing data access controls and permissions can help prevent unauthorized access to sensitive data. This can be achieved through Azure's data governance tools.

Data governance policies and procedures should be clearly defined and communicated to all stakeholders. This helps ensure that everyone is on the same page and working towards the same goals.

Data governance is not a one-time task, but rather an ongoing process. Regularly reviewing and updating data governance policies and procedures can help ensure that they remain effective and relevant.

By following these best practices, organizations can ensure that their data governance tools are being used effectively to maximize value. This can lead to improved decision-making, increased efficiency, and reduced risk.

Data governance is a practice that's nurtured over time, and it's essential to have a clear understanding of what it entails. Aggregated insights help put the "practice" into your data governance practice by showcasing the overall health of your governed data estate.

Built-in reports surface deep insights across various dimensions, including assets, catalog adoption, classifications, data governance, data stewardship, glossary, and sensitivity labels. This level of detail allows you to filter by business domain, data product, and status for even deeper insights.

Anchoring data governance investments to measurable business objectives and key results (OKRs) is crucial for aligning your data governance practice to business priorities. This approach enables organizations to demonstrate business value outcomes and accelerate the creation of responsible value from their data.

The new Microsoft Purview data governance experience is designed to help any organization, regardless of size, accelerate business value creation in the era of AI. This means that data governance is no longer just a technical aspect, but a business-driven initiative that's tailored to meet the unique needs of each organization.