This advanced KNIME workflow is designed for Supply Chain Analytics professionals to streamline the process of translating address data into geographic coordinates (latitude and longitude) using the Log-hub Supply Chain Apps geocoding service. The workflow leverages an efficient caching system to avoid redundant geocoding requests for already processed addresses, significantly speeding up the process when handling large datasets.
Key Steps of the Workflow:
1.) Input Address Data:
The workflow begins by importing address data (Country, State, Zip, City, Street) from an Excel file (or alternative sources), which serves as the geocoding input. Users need to provide a valid Supply Chain Apps API Key, Workspace ID, and Scenario Name to connect to the geocoding service.
2.) Caching Mechanism:
A Parquet-based cache stores previously geocoded results. The workflow checks if an address has been successfully geocoded in the past. If it exists in the cache, it is directly retrieved, bypassing the API call, saving time and API resources.
3.) Geocoding:
For new addresses, the workflow sends requests to the Log-hub geocoding service. The response returns the geographical coordinates (latitude, longitude) for each address.
4.) Handling Exceptions:
Addresses that could not be geocoded or did not meet the required quality thresholds are flagged for manual review. An exception-handling mechanism is in place to store these addresses for further analysis or correction.
5.) Visualization and Storage:
The final step of the workflow is to visualize the geocoded locations on a map. The map, along with the processed dataset, is saved to the Supply Chain Apps platform, enabling seamless access for further reporting or decision-making.
This workflow is ideal for logistics and supply chain professionals who need a scalable solution for geocoding large volumes of address data with built-in mechanisms to handle incomplete or problematic addresses. The caching and exception-handling processes ensure maximum efficiency and accuracy, while the API integration with Log-hub's platform allows for powerful geocoding, data visualization and storage.
Key Steps of the Workflow:
1.) Input Address Data:
The workflow begins by importing address data (Country, State, Zip, City, Street) from an Excel file (or alternative sources), which serves as the geocoding input. Users need to provide a valid Supply Chain Apps API Key, Workspace ID, and Scenario Name to connect to the geocoding service.
2.) Caching Mechanism:
A Parquet-based cache stores previously geocoded results. The workflow checks if an address has been successfully geocoded in the past. If it exists in the cache, it is directly retrieved, bypassing the API call, saving time and API resources.
3.) Geocoding:
For new addresses, the workflow sends requests to the Log-hub geocoding service. The response returns the geographical coordinates (latitude, longitude) for each address.
4.) Handling Exceptions:
Addresses that could not be geocoded or did not meet the required quality thresholds are flagged for manual review. An exception-handling mechanism is in place to store these addresses for further analysis or correction.
5.) Visualization and Storage:
The final step of the workflow is to visualize the geocoded locations on a map. The map, along with the processed dataset, is saved to the Supply Chain Apps platform, enabling seamless access for further reporting or decision-making.
This workflow is ideal for logistics and supply chain professionals who need a scalable solution for geocoding large volumes of address data with built-in mechanisms to handle incomplete or problematic addresses. The caching and exception-handling processes ensure maximum efficiency and accuracy, while the API integration with Log-hub's platform allows for powerful geocoding, data visualization and storage.