Getting Started With Analytics 2.0

The Analytics Cloud Connect Access tool is a command-line interface (CLI) that helps you configure and manage data transfers from Procore to MS SQL Server. It consists of two main components:

• user_exp.py (Configuration setup utility)

• delta_share_to_azure_panda.py(Data synchronization script)

• Python and pip installed on your system.

• Access to Procore Delta Share.

• MS SQL Server account credentials.

• Download the zipped package from the company level Analytics tool (via Analytics > Getting Started > Connection Options > SQL Server).

• Install required dependencies: pip install -r requirements.txt.

• Initial Configuration

• Data Synchronization

• Delta Share Configuration

• MS SQL Server Configuration

• SSIS Configuration

Initial Configuration

• Run the configuration utility: python user_exp.py

This will help you set up the following:

• Delta Share source configuration

• MS SQL Server target configuration

• Scheduling preferences

Data Synchronization

After configuration, you have two options to run the data sync:

1. Direct Execution python
   delta_share_to_azure_panda.py
   OR

2. Scheduled Execution
   If configured during setup, the job will run automatically according to your cron schedule.

Delta Share Configuration

1. Create a new file named config.share with your Delta Share credentials in JSON format.
   {
"shareCredentialsVersion": 1,
"bearerToken": "xxxxxxxxxxxxx",
"endpoint": "https://nvirginia.cloud.databricks.c...astores/xxxxxx"
}

2. Get required fields:
   Note: These details can be obtained from the Analytics web application.

   • ShareCredentialsVersion: Version number (currently 1).

   • BearerToken: Your Delta Share access token.

   • Endpoint: Your Delta Share endpoint URL.

   • Save the file in a secure location.

3. When configuring the data source, you'll be asked to provide:

   • List of tables (comma-separated).

   • Leave blank to sync all tables.

   • Example: table1, table2, table3.

   • Path to your config.share file.

MS SQL Server Configuration

You'll need to provide the following MS SQL Server details:

• database

• host

• password

• schema

• username

SSIS Configuration

1. Using the command line, navigate to the folder by entering 'cd '.

2. Install required packages using 'pip install -r requirements.txt' or 'python -m pip install -r requirements.txt'.

3. Open SSIS and create a new project.

4. From SSIS Toolbox, drag and drop 'Execute Process Task' activity.

5. Double-click on 'Execute Process Task' and navigate to Process tab.

6. In 'Executable', enter the path to python.exe in python installation folder.

7. In 'WorkingDirectory' enter a path to the folder containing the script you want to execute (without script file name).

8. In 'Arguments' enter the name of the script 'delta_share_to_azure_panda.py' you want to execute with the .py extension and save.

9. Click on 'Start' button in upper pane:

10. During the execution of the task, output of the Python console is displayed in the external console window.

11. Once the task is done it will display a green tick: