Explanation:

Box 1: Configure Evegent Hubs partitions
Scenario: Maximize the throughput of ingesting Twitter feeds from Event Hubs to Azure Storage without purchasing additional throughput or capacity units.
Event Hubs is designed to help with processing of large volumes of events. Event Hubs throughput is scaled by using partitions and throughput-unit allocations.
Event Hubs traffic is controlled by TUs (standard tier). Auto-inflate enables you to start small with the minimum required TUs you choose. The feature then scales automatically to the maximum limit of TUs you need, depending on the increase in your traffic.
Box 2: An Azure Data Lake Storage Gen2 account
Scenario: Ensure that the data store supports Azure AD-based access control down to the object level.
Azure Data Lake Storage Gen2 implements an access control model that supports both Azure role-based access control (Azure RBAC) and POSIX-like access control lists (ACLs).
Reference:
https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-features
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-access-control

Explanation:
Box 1: A security policy for sale
Here are the steps to create a security policy for Sales:
Create a user-defined function that returns the name of the current user:
CREATE FUNCTION dbo.GetCurrentUser()
RETURNS NVARCHAR(128)
AS
BEGIN
RETURN SUSER_SNAME();
END;
Create a security predicate function that filters the Sales table based on the current user:
CREATE FUNCTION dbo.SalesPredicate(@salesperson NVARCHAR(128))
RETURNS TABLE
WITH SCHEMABINDING
AS
RETURN SELECT 1 AS access_result
WHERE @salesperson = SalespersonName;
Create a security policy on the Sales table that uses the SalesPredicate function to filter the data:
CREATE SECURITY POLICY SalesFilter
ADD FILTER PREDICATE dbo.SalesPredicate(dbo.GetCurrentUser()) ON dbo.Sales WITH (STATE = ON); By creating a security policy for the Sales table, you ensure that each salesperson can only access their own sales data. The security policy uses a user-defined function to get the name of the current user and a security predicate function to filter the Sales table based on the current user.
Box 2: table-value function
to restrict row access by using row-level security, you need to create a table-valued function that returns a table of values that represent the rows that a user can access. You then use this function in a security policy that applies a predicate on the table.

Explanation:

Explanation:

Box 1: Hash
Scenario:
Ensure that queries joining and filtering sales transaction records based on product ID complete as quickly as possible.
A hash distributed table can deliver the highest query performance for joins and aggregations on large tables.
Box 2: Set the distribution column to the sales date.
Scenario: Partition data that contains sales transaction records. Partitions must be designed to provide efficient loads by month. Boundary values must belong to the partition on the right.
Reference:
https://rajanieshkaushikk.com/2020/09/09/how-to-choose-right-data-distribution-strategy-for-azure-synapse/

All file formats have different performance characteristics. For the fastest load, use compressed delimited text files.
Reference:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/guidance-for-loading-data