Stratsoft specializes in building and analyzing geo-economic databases. The resultant data are often depicted as maps because this is the most efficient way for decision-makers to absorb and use large data-sets. Once the data are in an electronic form it can be subjected to a variety of analysis routines that reveal new insight such as;

Our methods are based on rigorous quantitative methods developed over many years of practice. Stratsoft has originated a number of data development and analysis software programs to draw out new meaning and insight from data. We favor data that has high original reliability and cross-reference this with similar data in order to improve the integrity further.

Systematic, and often statistical, analysis combined with fully auditable data can yield powerful insight and a common information set that decision-makers can together use to plan strategy and represent opportunity to their stakeholders.

Some examples are provided as maps on this website and include the following.

 

 

Population Density

Perhaps the most basic data that nevertheless provides perspective on what 'national' really means. The actual clusters of the population do not correspond well to the Metropolitan Statistical Area (MSAs) boundaries and the bulk of the population is concentrated in some 4% of the land area. Geo-economic analysis reveals that cellsites follow the population almost exactly and thus give new perspective to the term "national coverage".

 

Population Density

 

Cellsite Backhaul in San Diego

This 'desktop' design provides data on cellsite location and tenancy with a network design that connects all sites back to the communications network. Quantification of sites, links, link distances and directions allows planners the ability to better envisage the feasibility of building a network as well as the 'what if' capability to explore alternatives. This map also reveals the significance of cellsite clustering with respect to the overall Basic Economic Area (BEA) license area.

 

Cellsite Backhaul in San Diego

 

National Neighborhood Network

How do houses cluster in the US? This map and associated charts show how cluster size of houses change depending on the distance between them and how many households decide to participate in this network. While the underlying data are from public sources the analysis reveals that cluster size changes dramatically as connection distances increase up to 300 meters but that beyond this distance the cluster size changes little. Inset maps show the wide route diversity possible for a network that connects these houses. Whether is Femto cell deployment, Machine-to-Machine communications, or a grass roots wireless network this analysis provides geo-economic insight into what is possible within the US household environment.

 

Los Angeles Addressable Housing Click, rollover to explore

 

Public Safety Points in East Boston

This map is an example of the types of granular data that can be available to the planner. Trees, street furniture, and buildings of different types all enable the planner to better understand the geo-spatial deployment environment and thereby reduce the chances of costly errors in the field.

 

Public Safety Points in East Boston

 

 

 


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