geobo | Python package for Multi-Objective Bayesian Optimisation

There is a Supply Management System that has been assigned to me, I have to study that for the customization request of the client. I have been searching for a while to find a possible solutions for my scenario. But still no luck, however I got a back up plan to do so.

Here's the details(My new PC):

My local SQL Server Name : DEV01\SQLExpress
Database : S_Premium - The database of the supply management system
GeoBos - This is dedicated for another system, I restored it for testing purposes to my local SQL Server Name.

S_Premium and GeoBos is dedicated to a different systems but the data being used is Integrated with each other.

Scenario:

I have been moved to another PC with another SQL Server. The S_Premium is using 50+ Views and Stored procedures which some of their queries is integrated to the servername of GeoBos(Example Above).

S_Premium Views query example:

SELECT DISTINCT ..... FROM LnkdSrvrBOSS.GEOBOS.BOS.T_OBR_Hdr

LnkdSrvrBOSS - came from GeoBos previous server name
GeoBos - database name
BOS.T_OBR_Hdr - is a table under database "GeoBos"

What I did is deleting the LnkdSrvrBOSS manualy for every Views/Stored Procedures(It worked), But my problem is I have to do it manually for all Views and stored procedures that causing me a long time process.

Question:

1.) Is there a query that can replace or update the "LnkdSrvrBOSS" of "SELECT DISTINCT ..... FROM LnkdSrvrBOSS.GEOBOS.BOS.T_OBR_Hdr" from Views/Stored Procedure ?

2.) Do I really have to delete the "LnkdSrvrBOSS" manually(One by one)?

3.) Or should I create a another SQL Server name "LnkdSrvrBOSS" and restore the database in there?

Thank you!