Telco
Estimate population covered by a telecommunications cell network
This example demonstrates how to use Workflows to estimate the total population covered by a telecommunications cell network, by creating areas of coverage for each antenna, creating an H3 grid and enriching it with data from the CARTO Spatial Features dataset.
CARTO DW | BigQuery | Snowflake | Redshift | PostgreSQL |
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Mobile pings within Area of Interest
This example demonstrates how to use Workflows to find which mobile devices are close to a set of specific locations, in this case, supermarkets of competing brands.
CARTO DW | BigQuery | Snowflake | Redshift | PostgreSQL |
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Population Statistics
This example demonstrates how to use Workflows to carry on with a common analysis for telco providers: analyze their coverage both by area (i.e. square kilometers) and by population covered.
In this analysis we will analyze the coverage for AT&T LTE Voice based on the public data from the Federal Communications Commission FCC.
CARTO DW | BigQuery | Snowflake | Redshift | PostgreSQL |
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Emergency Response
This example demonstrates how to use Workflows to leverage Telco providers' advanced capabilities to respond to natural disasters. Providers can use geospatial data to better detect at risk areas for specific storms. In this analysis we will analyze buildings and cell towers in New Orleans to find clusters of at risk buildings for flooding and potential outages.
CARTO DW | BigQuery | Snowflake | Redshift | PostgreSQL |
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New tower site selection in Denver
Selecting a new location for a tower requires understanding where customers and coverage gaps are, however, we can also identify buildings that might be suitable for a new tower. We do that in this analysis.
CARTO DW | BigQuery | Snowflake | Redshift | PostgreSQL |
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