Connecting to SQL data source with real-time data polling
This is a simple demonstration of how we can use atoti to analyse sales of medical devices.
The notebook also shows two different authentication mechanisms that we can integrate with the Atoti+ plugin.
Contact [email protected] if you need more information on Atoti+.
Alternative, you can comment off the security related codes to run the notebook with Atoti+ plugin.
This example uses mock data. Depending on whether you are using the CSV version or SQL connector version of the use case, the data source used is different.
For CSV example: Refer to the data files under the data directory:
For MS SQL example: Use 00_data_generation.ipynb to generate and upload data into MS-SQL database. Update the database JDBC URL according to your own database setting.
The data is generated using the below data templates:
Use 01_main_csv.ipynb to run analysis by consuming CSV data files.
Use 02_main_mssql_realtime.ipynb to run analysis by loading data from MS SQL database into the atoti data cube. This notebooks includes demonstration of:
- Security implementation with basic authentication
- atoti connectivity to SQL database
- real-time dashboarding, polling delta data from the database
- what-if simulation (replace mockML.py with your own machine learning algorithm to forecast the sales in the next quarter.
- Cumulative trends and YTD/YTM computation
03_main_LDAP_authentication.ipynb shows how to connect to an LDAP authentication provider.