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Database management is fundamental in every organization. It ensures data consistency, integrity, accuracy, and security. One crucial aspect of DBMS is SQL Data Governance. This blog post will provide you with some best practices to follow when using Databricks for SQL Data Governance.
Understanding Data Governance in Databricks
Databricks is a powerful analytics platform fully optimized for Azure’s infrastructure service, with added security and compliance benefits intrinsic from Azure. It offers an interactive workspace where data engineers, data scientists, and business analysts can work together using SQL, Python, R, and Scala.
SQL Data Governance Best Practices
Now let’s dive into the following SQL Data Governance best practices and understand how they ensure compliance and security.
1. Understanding and Defining Data
First, organizations must have a clear understanding and definition of the data they handle. Various types of data require different governance techniques.
2. Organizing Data Securely
Organize and structure your data in tables and schemas appropriately, taking into consideration the principle of least privilege. Keep related data in the same schema, but make use of separate schemas where it makes sense, for example to enforce different security requirements.
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CREATE SCHEMA Sales; CREATE TABLE Sales.Orders (OrderID int, OrderDate date); |
Note:
The above SQL code creates a schema titled ‘Sales’ and an ‘Orders’ table within it.
3. Implementing Access Control Strategies
Managing who has access to what data is another crucial aspect of data governance. Organizations should have proper access control strategies and security policies in place.
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CREATE USER TestUser WITHOUT LOGIN; GRANT SELECT ON Sales.Orders TO TestUser; |
Note:
The above SQL code creates a user ‘TestUser’ and grants them select access to the ‘Orders’ table under the ‘Sales’ schema.
4. Understanding Compliance and Security Laws
It is essential for organizations to understand the compliance and security laws applicable to them, such as GDPR. Non-compliance can lead to heavy penalties.
5. Regular Monitoring and Auditing
Regular monitoring of data usage trends and regular audits to check who accessed what data and when is a good practice to spot any data misuse.
The Bottom Line
Combining Databricks and SQL to manage your organization’s data can prove very powerful, ensuring high standards of compliance and security. Though implementing the above mentioned SQL Data Governance best practices is crucial, it’s equally important to adapt these practices to fit the specifics of your organization’s Data Governance requirements.