Spectrum Spatial (SSA/LIM)

MapInfo Pro is a great tool for analyzing Telco data, however sharing data across the business often requires a web mapping solution. Spectrum Spatial Analyst is a great way of simply publishing from the desktop to the web. Did you know that Spectrum Spatial Analyst(SSA) can also publish big data directly from the mobile network? This can be done using SSA and PB's Big Data LI API's. Imagine being able to quickly geocode 9 billion call records in to a scalable map, aggregated into thematically covered hexagons showing KPI's such as call quality, data rate or number of calls per area. This insight benefits all areas of the business from network ops to sales, marketing and customer service.

See Attachment

The map above shows tweets aggregated and counted inside scaling hexagons. The green areas showing the highest number of tweets, red showing lower numbers. It's interesting to view the higher numbers around city areas, what is also interesting is to consider the difference in the time of day between to the East and West coast. A density pattern can be clearly seen across the US directly related to the time of day. When data of this volume can be visualized and spatially queried in near real-time a host of new insight can be achieved.

I've seen some great visualizations of telco data during the eclipse - great stuff.

Hello Chris, 

How did you manage to do this using BigData? Do you have the methodology to achieve these kinds of data visualizations ?

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Krishna Bejawada
Nityo Infotech Services Pte Ltd
Singapore
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Original Message:
Sent: 08-18-2017 04:44
From: Chris Jenkins
Subject: Visualizing real-time network data in Spectrum Spatial Analyst

MapInfo Pro is a great tool for analyzing Telco data, however sharing data across the business often requires a web mapping solution. Spectrum Spatial Analyst is a great way of simply publishing from the desktop to the web. Did you know that Spectrum Spatial Analyst(SSA) can also publish big data directly from the mobile network? This can be done using SSA and PB's Big Data LI API's. Imagine being able to quickly geocode 9 billion call records in to a scalable map, aggregated into thematically covered hexagons showing KPI's such as call quality, data rate or number of calls per area. This insight benefits all areas of the business from network ops to sales, marketing and customer service.

See Attachment

The map above shows tweets aggregated and counted inside scaling hexagons. The green areas showing the highest number of tweets, red showing lower numbers. It's interesting to view the higher numbers around city areas, what is also interesting is to consider the difference in the time of day between to the East and West coast. A density pattern can be clearly seen across the US directly related to the time of day. When data of this volume can be visualized and spatially queried in near real-time a host of new insight can be achieved.