PowerShell Instructions
If you are configuring your own server, continue with the steps below to run the PowerShell script.
Setup
First, make sure you have set up your SQL Server. Then proceed with the steps below to run the solution template using the automated PowerShell files.
Execute PowerShell Script
Running this PowerShell script will create the data tables and stored procedures for the the operationalization of this solution in R in the LoanChargeOff_R
database. It will also execute these procedures to create full database with results of the steps – dataset creation, modeling, and scoring as described here.
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Log onto the computer that contains the SQL Server you wish to use.
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Install Git if it is not already present. During the install, check the box to add LFS support.
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Download LoanChargeOffSetup.ps1 to your computer.
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Open a command or PowerShell window as Administrator.
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CD to the directory where you downloaded the above .ps1 file and execute the command:
.\LoanChargeOffSetup.ps1
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Make sure to accept installation of NuGet if prompted.
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This will make the following modification to your SQL Server:
- Installs the SQL Server PowerShell module. If this is already installed, it will update it if necessary.
- Creates the SLQRUserGroup for running R and Python code.
- Reconfigures SQL Server to allow running of external scripts.
- Clones the solution code and data into the c:\Solutions\LoanChargeOff directory
- Creates the solution database
LoanChargeOff_R
and configures an ODBC connection to the database. - Executes the stored procedure
Initial_Run_Once_R
to run the entire workflow for this solution.
Review Data
Once the PowerShell script has completed successfully, log into the SQL Server Management Studio to view all the datasets that have been created in the LoanChargeOff
database.
Hit Refresh
if necessary.
Click here to view more information about each of these tables.
Right click on dbo.vw_loan_chargeoff_prediction
and select View Top 1000 Rows
to preview the scored data.
Click here to view the details all tables created in this solution.
Visualizing Results
You’ve now created and processed data, created models, picked the best one and used the model to predict loan chargeoff as described here. This PowerShell script also created the stored procedures that can be used to score new data for the new loans.
Let’s look at our current results. Proceed to Visualizing Results with PowerBI.
Other Steps
You’ve just completed the fully automated solution that simulates the data, trains and scores the models, and provide recommendations by executing PowerShell scripts.
See the Typical Workflow for a description of how these files were first created in R by a Data Scientist and then incorporated into the SQL stored procedures that you just deployed.