In this article, we will demonstrate how to import tables from a CSV file, perform geolocation lookup through transformations, and move the cleaned data into the destination database using Bold Data Hub. Follow the step-by-step process below.
Sample Data Source:
Sample Customers Data
Geo Lookup
Note: On-Demand Refresh will be triggered when the pipeline is saved. If needed, the pipeline can be scheduled in the Schedules tab.
Go to the Transform tab and click Add Table.
Enter the table name to create a transform table for customer satisfaction summary.
Note: The data will initially be transferred to the DuckDB database within the designated {pipeline_name} schema before undergoing transformation for integration into the target databases. As an illustration, in the case of a pipeline named “customer_service_data”, the data will be relocated to the customer_service_data table schema.
Learn more about transformation here
Enhancing customer data with geographic details using IP addresses or zip codes helps in location-based analysis, fraud detection, and personalized customer experiences.
We use a LEFT JOIN
to match customer IP addresses against a geolocation lookup table. The BETWEEN
condition ensures that the IP falls within a known IP range.
SELECT
c.customer_id,
c.name,
c.email,
c.ip_address,
g.country,
g.state,
g.city
FROM {pipeline_name}.sample_customers_data c
LEFT JOIN {pipeline_name}.geo_lookup g
ON c.ip_address BETWEEN g.ip_start AND g.ip_end;