Sql-server – Is SQL Server sp_who2 deprecated

I think you are misreading the deprecation notice. Specifically, you seem to be confusing DML (Data Modification Language) with DDL (Data Definition Language). What is being deprecated is the ability to use ROWGUIDCOL in INSERT / UPDATE / DELETE / MERGE statements:

-- DDL statement
CREATE TABLE #Test
(
  ID UNIQUEIDENTIFIER NOT NULL PRIMARY KEY DEFAULT (NEWID()) ROWGUIDCOL,
  SomeColumn INT NULL
);

INSERT INTO #Test ([SomeColumn]) VALUES (1), (100);

SELECT * FROM #Test;

DECLARE @RowID UNIQUEIDENTIFIER;
SELECT TOP 1 @RowID = tbl.[ID]
FROM   #Test tbl;

SELECT @RowID AS [RowToUpdate];

-- DML statement
UPDATE tmp
SET    tmp.[SomeColumn] += 2
FROM   #Test tmp
WHERE  ROWGUIDCOL = @RowID;

SELECT * FROM #Test;

If you run the above, only one row will be updated. This example shows that ROWGUIDCOL when used in a DML statement (not in a DDL statement) is dynamically replaced with the actual column marked as ROWGUIDCOL. And this is, in fact, why you are able (or required?) to mark a column as ROWGUIDCOL in a DDL statement: so that you (and other processes) can find it later :-).

Possible a slightly subjective question but sometimes it's helpful to think of these things in scenarios, for example:

1. A predominantly SQL Server project, run by DBAs/devs (who may or may not know some R). A data scientist or R professional writes some R for them or they do it themselves and test on their local machines, eg using R Studio or the Microsoft R IDE. When they are happy with the R, they plug it into their data workflow using sp_execute_external_script. They can easily incorporate this into other stored procedures, SSIS etc. This might be a good candidate for SQL Server 2016 with R Services.
2. A secure project, the data is in your secured SQL Server and you want to keep the data close to the analytics and not use the cloud. This might be a good candidate for an on-premise installation of SQL Server 2016 with R Services.
3. A predominantly data science project which requires data but does not require SQL Server access. This might be a good candidate for Microsoft R Server only.
4. High performance is required for a big data project. You do not want to share the box with the traditionally memory-hungry SQL Server. This might be a good candidate for Microsoft R Server only.

Just a few examples there. What examples can you think of?

HTH