Cloud Analytics, Big Data Analytics: The Sky’s the Limit for Spatial and Geo-Location Analytics

Continuing the general Big Data Analytics and Cloud Analytics theme, this TDWI article lists 11 predictions for Big Data.  The article points to an increased focus on chips, over hardware, citing a huge gap between chips and business software.  Put simply, more chips are needed to process the exponential data growth far more efficiently.  Predictions indicate a single modern chip may be able to run up to 512 cores, and that’s going to dramatically reduce hardware n

Continuing the general Big Data Analytics and Cloud Analytics theme, this TDWI article lists 11 predictions for Big Data.  The article points to an increased focus on chips, over hardware, citing a huge gap between chips and business software.  Put simply, more chips are needed to process the exponential data growth far more efficiently.  Predictions indicate a single modern chip may be able to run up to 512 cores, and that’s going to dramatically reduce hardware necessary to manage data networks.  The new technology, when it emerges, will offer a more efficient option to traditional massively parallel processing solutions.  Other trends include increased focus on analytics, in-house analytical solutions, a hybrid model utilizing open-source and commercial or proprietary analytical tools.

 The Summer 2011 Esri ArcNews publication features a special cloud issue.  ArcGIS Online is developing a cloud-based system for map and geo-location information sharing.  The growing importance of cloud comping for GIS focuses on reduced costs, flexibility, scalability and rapid deployment.  ArcGIS Online can be used by anyone to create maps that will integrate with most devices, embed maps into sites and web applications.  By moving to a cloud-based system, it’s possible to create an information-sharing platform for map-combination, accessible through APIs and free viewers.  The system is based on thousands of geo-spatial datasets.  The platform is searchable by keywords and maps can be enhanced by users wanting to add new dimensions and views to standard map views.  It’s all served up in a SaaS application, where users create and share the maps and data and perform sophisticated geospatial analysis in a cloud-based environment.

Here’s an interesting geo-location add-on to Google Analytics called InstaVista.  It runs on top of Google Analytics and allows real-time or historical visualization of online and multi-channel data in cloud-based dashboard system.