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Data Governance is a crucial aspect when it comes to managing large-scale data in the IT industry. With Databricks becoming a common platform, it becomes even more important to ensure the governance and compliance of data stored in SQL databases hosted on Databricks. In this blog, we will delve into the importance of SQL Data Governance and how it can be maintained in Databricks.
What is Data Governance?
Data Governance is the overall management of the availability, usability, integrity, and security of data used in an enterprise. It’s a collection of practices and processes which help to ensure the formal management of data assets within an organization.
Ensuring Compliance with SQL Data Governance in Databricks
In the context of Databricks, SQL data governance can be achieved by setting rules, restrictions, and permissions on the SQL databases. Let’s take a simple example of a SELECT query and see how it conforms to our data governance rules.
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-- A typical SELECT statement SELECT * FROM Employees; |
This query retrieves all records from the Employees table. But consider a scenario where, according to our Data Governance rule, a user should only access data of employees from the department they belong to. In such a case, our query should look like this:
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-- A SELECT statement with WHERE clause, adhering to the Data Governance rules SELECT * FROM Employees WHERE DepartmentId = 'D001'; |
The above SQL code is a perfect example of implementing data governance using a WHERE clause to restrict the data being accessed.
Managing Roles and Permissions
In Databricks, we can also manage roles and permissions to ensure SQL data governance. The GRANT and REVOKE commands are used to manage privileges.
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-- GRANT PRIVILEGES GRANT SELECT, INSERT, UPDATE, DELETE ON Employees TO HR_Role; -- REVOKE PRIVILEGES REVOKE UPDATE, DELETE ON Employees FROM HR_Role; |
In the above example, the HR_Role is granted SELECT, INSERT, UPDATE, and DELETE privileges on the Employees table. Later, the UPDATE and DELETE privileges are taken back, ensuring tighter control on who can modify the data.
Conclusion
By implementing SQL Data Governance in Databricks, organizations can ensure better control, management, and optimization of their data assets. It helps them to stay in compliance with the various laws and regulations while providing better security and quality of their data.