Explanation
Graphical user interface, text, application, chat or text message Description automatically generated

Step 1: Create RangeStart and RangeEndDateTime parameters.
When configuring incremental refresh in Power BI Desktop, you first create two Power Query date/time parameters with the reserved, case-sensitive names RangeStart and RangeEnd. These parameters, defined in the Manage Parameters dialog in Power Query Editor are initially used to filter the data loaded into the Power BI Desktop model table to include only those rows with a date/time within that period.
Step 2: Add an applied step that adds a custom date filter OrderDate is Between RangeStart and RangeEnd.
With RangeStart and RangeEnd parameters defined, you then apply custom Date filters on your table's date column. The filters you apply select a subset of data that will be loaded into the model when you click Apply.
Step 3: Configure an incremental refresh to archive data that starts two years before the refresh date.
After filters have been applied and a subset of data has been loaded into the model, you then define an incremental refresh policy for the table. After the model is published to the service, the policy is used by the service to create and manage table partitions and perform refresh operations. To define the policy, you will use the Incremental refresh and real-time data dialog box to specify both required settings and optional settings.
Step 4: Add an applied step that filters OrderDate to the start of the prior year.
Reference: https://docs.microsoft.com/en-us/power-bi/connect-data/incremental-refresh-overview

Explanation
Using the compute engine to improve performance
Take the following steps to enable workloads trigger the compute engine, and always improve performance:
For computed and linked entities in the same workspace:
Ensure you perform the operations that fold, such as merges, joins, conversion, and others.
For ingestion focus on getting the data into the storage as fast as possible, using filters only if they reduce the overall dataset size. It's best practice to keep your transformation logic separate from this step, and allow the engine to focus on the initial gathering of ingredients. Next, separate your transformation and business logic into a separate dataflow in the same workspace, using linked or computed entities; doing so allows for the engine to activate and accelerate your computations. In our analogy, it's like food preparation in the kitchen:
food preparation is typically a separate and distinct step from gathering your raw ingredients, and a pre-requisite for putting the food in the oven. Similarly, your logic needs to be prepared separately before it can take advantage of the compute engine.
Reference:
https://docs.microsoft.com/en-us/power-bi/transform-model/dataflows/dataflows-premium-workload-configurati

Explanation
Solution: From DAX Studio, you write a query that uses grouping sets.
A grouping is a set of discrete values that are used to group measure fields.
Reference: https://docs.microsoft.com/en-us/power-bi/developer/visuals/capabilities

Explanation
Solution: You recommend using OPENROWSET WITH to explicitly specify the maximum length for businessName and surveyName.
The size of the varchar(8000) columns are too big. Better reduce their size.
A SELECT...FROM OPENROWSET(BULK...) statement queries the data in a file directly, without importing the data into a table. SELECT...FROM OPENROWSET(BULK...) statements can also list bulk-column aliases by using a format file to specify column names, and also data types.
Reference: https://docs.microsoft.com/en-us/sql/t-sql/functions/openrowset-transact-sql

Explanation
Assigning workspaces to capacities
Workspaces can be assigned to a Premium capacity in the Power BI Admin portal or, for a workspace, in the Workspace pane.
Note: Capacity limits
Workspace storage limits, whether for My Workspace or an app workspace, depend on whether the workspace is in shared or Premium capacity.
* Shared capacity limits
For workspaces in shared capacity:
There is a per-workspace storage limit of 10 GB.
Premium Per User (PPU) tenants have a 100 TB storage limit.
When using a Pro license, the total usage can't exceed the tenant storage limit of 10 GB multiplied by the number of Pro licenses in the tenant.
* Premium capacity limits
For workspaces in Premium capacity:
There is a limit of 100 TB per Premium capacity.
There is no per-user storage limit.
Workspace storage usage is shown as 0 (as shown in this screenshot) if the workspace is assigned to a Premium capacity.
Incorrect:
Not C: If your organization is using the original version of Power BI Premium, you're required to migrate to the modern Premium Gen2 platform. Microsoft began migrating all Premium capacities to Gen2.
Reference: https://docs.microsoft.com/en-us/power-bi/enterprise/service-premium-capacity-manage-gen2
https://docs.microsoft.com/en-us/power-bi/admin/service-admin-manage-your-data-storage-in-power-bi