• ArcGIS GeoAnalytics Engine brings the power of spatial analysis to existing big data infrastructures, helping analysts make sense of big spatial data quickly and easily.
• This demonstration from David Yu shows how ArcGIS GeoAnalytics Engine can help you process and analyze large amounts of telecom data to better understand where we may be able to discover underserved areas and bridge the digital divide.
• Using ArcGIS GeoAnalytics Engine to run spatial analysis on tens of millions of anonymized Ookla records from cell phones in the United States, telecom operators can visualize where their networks have the best coverage and optimized performance, as well as understand the areas that are underserved.
• To run spatial analysis on a large volume of data, leverage the power of distributed processing with Spark in a big data environment in the cloud. ArcGIS GeoAnalytics Engine includes more than 100 spatial functions native to Spark SQL and geoanalytics tools are accessible through pySpark, allowing for spatial functions to be run within an existing big data environment.
• Big data can be clustered, shared to ArcGIS Online and published on a web map for additional insights. Taking a closer look, we found that the national forests and wildlife refuges in the rural areas of southern Oregon could give us additional awareness to coverage deficiencies in the area.
• Network providers and public utility commissions can view results on a web app to better understand the digital divide. Aggregate data can be filtered to understand where disadvantaged communities and indigenous population reservations may have poor coverage, as well as where providers should prioritize network investments.
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