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Welcome to SQLSupport.org's deep dive into SSRS Dataset Parameters vs Report Parameters in the context of SQL Server 2022 and Azure SQL. As we traverse through the world of SQL reporting, it's essential to understand the difference between these two types of parameters, which play a pivotal role in SQL Server Reporting Services (SSRS).

Let's start with Dataset Parameters. These are used to filter data at the dataset level, not at the report level. When a query is executed against a database, dataset parameters are passed to the query to determine what data should be returned. This is particularly efficient when dealing with large datasets, as it limits the amount of data that needs to be transferred from the database to the report server. Here's an example of how you might use a dataset parameter in T-SQL:

-- Define a parameter for the dataset
DECLARE @CustomerID INT;
-- Set the parameter value
SET @CustomerID = 123;
-- Use the parameter in the query
SELECT * FROM Customers WHERE ID = @CustomerID;

On the other hand, Report Parameters are used to control report data, affect report presentation, and are often used to interact with end users. They are not directly tied to database queries, but can be used to pass values to Dataset Parameters or to control report presentation. Here's an example of how you might use a report parameter in an SSRS report:

-- Define a report parameter
@ReportParameter1 AS INT;
-- Set the parameter value
SET @ReportParameter1 = 123;
-- Use the parameter to control report presentation
IF @ReportParameter1 = 123
BEGIN
    -- Show the detailed report
    EXEC ShowDetailedReport;
END
ELSE
BEGIN
    -- Show the summary report
    EXEC ShowSummaryReport;
END

In the new era of big data analytics, integrating SSRS with Azure SQL, Microsoft Fabric, and Delta Lake can provide an efficient and scalable reporting solution. Delta Lake, an open-source storage layer, brings reliability to data lakes by providing ACID transactions, scalable metadata handling, and unifies batch and streaming data processing. With Microsoft Fabric, data can be processed in parallel across a distributed network, allowing for massive scalability.

In conjunction with these technologies, OpenAI and SQL provide a powerful tool for generating reports. By using OpenAI's GPT-3, you can generate natural language queries to extract data from your SQL databases. This combination allows for a more intuitive and user-friendly reporting experience. Similarly, integrating Databricks with SSRS can enable advanced analytics within your reports, leveraging the power of Spark and Delta Lake.

In conclusion, understanding and properly leveraging Dataset Parameters and Report Parameters in SSRS can dramatically enhance your reporting capabilities. When combined with modern technologies like Azure SQL, Microsoft Fabric, Delta Lake, OpenAI, and Databricks, the possibilities for efficient, scalable, and user-friendly reports are virtually limitless.