Implementing enterprise-scale security in analytics solutions is paramount to ensure data integrity and confidentiality. One of the primary methods to implement this in Azure and Power BI is through row-level security (RLS) and object-level security (OLS). Let’s delve into details and understand what these security measures are and how they are implemented.
Row-Level Security (RLS)
Row-Level Security (RLS) provides a method to control access to rows in a database based on user characteristics such as identity, role, or execution context. RLS is an excellent way to restrict data access at the row level based on user roles, department, hierarchy, or other business rules.
For example, an HR specialist should only be able to see employee records that they manage, although technically they share the same underlying database with other HR specialists in the organization.
Implementation of RLS in Azure SQL Database
In the Azure SQL Database, you can implement RLS in tables by using security predicates – the function created inline during the creation of a security policy.
The following is an example of the predicate function and security policy:
CREATE SCHEMA Security;
GO
CREATE FUNCTION Security.fn_securitypredicate(@SalesRep AS sysname)
RETURNS TABLE
WITH SCHEMABINDING
AS
RETURN SELECT 1 AS fn_securitypredicate_result WHERE @SalesRep = USER_NAME();
GO
CREATE SECURITY POLICY SalesFilter
ADD FILTER PREDICATE Security.fn_securitypredicate(SalesRep)
ON dbo.Orders
WITH (STATE = ON);
GO
In the above SQL script, a filter predicate is added to the `Orders` table, which restricts the rows visible to a specific `SalesRep`.
Implementation of RLS in Power BI
In Power BI, you can create roles within the Power BI Desktop and define DAX expressions for these roles.
- Open Power BI Desktop, and load your data.
- Go to the ‘Modeling’ Tab and click on ‘Manage Roles’.
- Click on ‘Create’ to create a new role, and give it a meaningful name.
- Choose the table and column you want to implement RLS on, and define a DAX expression.
- Click on ‘Save’ to save the role and close the ‘Manage Roles’ window.
- Publish your report to Power BI service.
For example, if you wanted to filter the Sales data by region, the DAX expression would look like this:
[Region] = “WEST”
Object-Level Security (OLS)
Object-level security allows you to limit the visibility of specific tables or columns in a model. This ensures more granular control and helps protect sensitive information, especially when dealing with analysts who don’t need visibility onto every element of business data.
Implementation of OLS in Power BI
The implementation of Object-level security is relatively new in Power BI and as of now, can only be implemented via Tabular Editor, an advanced data model design tool for Power BI.
Here’s a high-level guide on how to implement OLS in Power BI:
- Open your Power BI report in Tabular Editor.
- Under ‘Roles’, define the restrictions for your table or column.
- After defining all restrictions, save changes to your model metadata.
- Back in Power BI Desktop, refresh the data to see the applied roles.
For example, to hide a sensitive column ‘Salary’ in the ‘Employees’ table, you would apply the following:
TablePermission Employees {
OLS columns {
ColumnPermission Salary {
hide = true;
}
}
}
Both Row-Level Security (RLS) and Object-Level Security (OLS) are potent tools when it comes to providing fine-tuned security options in your data models. Through consistent practice and application, you can master both of these to design and implement enterprise-scale analytics solutions using Microsoft Azure and Power BI.
Please note that while RLS and OLS ensure data visibility control, additional security measures like data masking, encryption, and maintaining least privilege access should be part of a comprehensive data security strategy.
Practice Test
True or False: Row-level security (RLS) can control access to rows in a database table based on characteristics of the user.
- True
- False
Answer: True
Explanation: Row-level security enables you to use group membership or execute logic to decide whether to return data to a user at runtime.
In designing and implementing enterprise-scale row-level security, you can use Azure Active Directory to manage access to resources.
- True
- False
Answer: True
Explanation: Azure Active Directory provides identity services that applications use for authentication and authorization to access resources.
How would you implement object-level security in Power BI?
- A. By restricting access to certain columns in a table
- B. By limiting access to certain rows in a table
- C. By hiding certain visualizations in a report
Answer: A. By restricting access to certain columns in a table
Explanation: Object-Level Security (OLS) in Power BI restricts data access at the column level of tables.
True or False: Object-Level Security (OLS) restricts data access at the row level of tables.
- True
- False
Answer: False
Explanation: It is Row-Level Security that restricts access at row level, while Object-Level Security restricts data access at the column level.
In Power BI, direct query datasets don’t support object-level security.
- A. True
- B. False
Answer: B. False
Explanation: From Power BI Premium and Power BI Premium per user workspace versions, you can secure your DirectQuery datasets with Object-level security.
True or False: Row-level security is a feature that allows for the control of access to items at the table level.
- True
- False
Answer: False
Explanation: Row-level security allows for control of access at the row level within a table, not the table level.
In designing and implementing row-level security, which of these features should you use?
- A. RBAC with Azure AD
- B. Object-level security
- C. Filtering in Power BI
Answer: A. RBAC with Azure AD
Explanation: Row-level security can be implemented using Role-Based Access Control (RBAC) with Azure Active Directory.
Select the correct statement:
- A. Object-Level security can restricted to the whole table
- B. Object-Level security can’t restrict access at the column level
- C. Object-Level security can provide selective access to tables within a dataset.
Answer: C. Object-Level security can provide selective access to tables within a dataset.
Explanation: Object-Level security is designed to provide selective access to tables within a dataset by restricting access at the column level.
Which of the following Azure features allows you to manage access, secure data, and scale your applications?
- A. Azure RBAC
- B. Azure AD
- C. Azure Storage
Answer: B. Azure AD
Explanation: Azure Active Directory is an Identity and Access Management (IAM) service that helps to manage access, secure data, and scale applications.
Power BI service supports which kind of security methods?
- A. Row-level security
- B. Object-level security
- C. Both A and B
Answer: C. Both A and B
Explanation: Power BI supports both Row-level and Object-level securities which restrict access to certain rows or columns in a table based on user roles.
Interview Questions
What is row-level security in enterprise-scale applications?
Row-level security (RLS) in enterprise-scale applications is a data security strategy that restricts data access at the row level within a database. Users can only access data in rows that they have permissions to view, ensuring the confidentiality of data.
What tools do Microsoft Azure and Power BI offer to implement row-level security?
Microsoft Azure offers Azure SQL Database for implementing row-level security. In Power BI, row-level security can be implemented using roles and row-level security filters.
What is object-level security in enterprise-scale applications?
Object-level security is a security model that controls a user’s access to individual objects within a database such as tables, views, or stored procedures. This is crucial in enterprises where different users need access to different objects.
How can you implement object-level security in Microsoft Azure?
Object-level security can be implemented in Microsoft Azure using Azure Role Based Access Control. This tool allows you to provide specific permissions to access and manipulate specific objects to specific users or groups.
How do you set up row-level security in Power BI?
You can set up row-level security in Power BI by creating roles and defining rules for each role under the Row-Level Security option in the dataset options.
Is it possible to add multiple filters to a role in Power BI’s row-level security?
Yes, it is possible to add multiple filters to a role when implementing row-level security in Power BI.
Can row-level security set in Power BI impact the performance of the Power BI report?
Yes, the implementation of row-level security can affect the performance of a Power BI report since the data is filtered based on user roles.
How is row-level security implemented in Azure SQL Database?
Row-level security in Azure SQL Database is implemented by enabling it on a database, creating an inline table valued function that determines access and then attaching that function to a specific table using a security policy.
What are the benefits of implementing object-level security in enterprise-scale applications?
Implementing object-level security prevents unauthorized access to data by ensuring users can only access the objects they require, adds an additional layer of security to data, and provides more granular control over data access.
What are the considerations while implementing Row-level Security in Power BI service?
While implementing Row-level Security in Power BI service, it is important to consider the impact on performance, confidentiality of data, complexity of managing multiple roles and filters, and the need for regular monitoring and updating to maintain security.
Can you assign multiple roles to a single user in row-level security in Power BI?
Yes, in Power Bi’s row-level security it is possible to assign multiple roles to a single user.
Can you test the row-level security setup in Power BI?
Yes, Power BI provides an option to ‘view as roles’ for testing the row-level security setup.
What is the purpose of the CHECK_ACCESS function in Azure SQL Database?
The purpose of CHECK_ACCESS function in Azure SQL Database is to permit or block access to rows of data based on the assessment of the user’s identity. It comes into play while implementing row-level security.
What is the impact of row-level security on DirectQuery in Power BI?
In DirectQuery, row-level security impacts the queries sent to the underlying data source. Power BI appends the row-level security filter to the query, so only rows that meet the filter conditions are returned.
Can the row-level security rules in Power BI access data from other tables?
No, row-level security rules in Power BI cannot access data from other tables. The rules can only refer to columns in the table to which they are applied.