Geoanalytics or geoanalysis, is a field of study that applies geographical concepts and machine learning methods to the analysis of information. Geoanalytics is an emerging science where big data technology extracts patterns, meaning and insights from complex geospatial datasets. It is a layer of geographical data added to business datasets. Hence it is also called Location Analytics, or location intelligence. Geoanalytics is a form of data visualization that contextualizes your data and uncovers insights through geographic location.
How does Geoanalytics work
Geoanalytics layers the datasets on a map to help to compare the data based on geographic boundaries. When the records are placed on a map, then we can see the big picture. Using advanced visualization techniques, it becomes easy to detect trends and patterns.
The Geoanalytics server provides a diverse collection of analysis tools that enable you to quickly analyze your data across space and time. These platforms allow the integration of Python commands and other API inclusions. Besides, database management can be conducted from within the platform and created with feature layers in raster or vector formats. This depends on the type of data which is plotted. By using feature layers, these servers can pinpoint exactly where collections of these target consumers live, work and spend most of their time. Correctly targeting the lucrative market wouldn’t have been possible without this mapping component.
Benefits of Geoanalytics
Geoanalytics layers data to enable comparisons among different locations. This helps identify trends and patterns across cities, regions, and countries. Understanding geospatial impacts on the business is critical for success in today’s global economy. Business entities that use location analytics to assess their business strategies can decrease costs, locate new sales opportunities, and implement changes for operational efficiency. Additionally, location analytics is highly visual and therefore easier for non-experts to understand insights found in the data.
GeoAnalytics Server tools can merge, join and manage different datasets. It does not matter where it is stored. The server works can harness many data sources, from Hadoop Distributed File System (HDFS) to cloud stores and existing GIS data. They can mix and match analysis inputs and outputs based on business requirements. It can also write your results to a feature layer which you can directly visualize on a map or write to a CSV you can store in the cloud. It has the capability to run multiple analysis in one pass instead of multiple batches. Since these geoanalysis servers crunch through Bigdata at a short time, you can save time to visualize, share and deduce your results.
Areas of Application
Organizations are already using geoanalytics in a variety of ways. From moving vehicles to social media, here are some of the applications of geoanalytics.
Healthcare, Life Science. Healthcare organizations can optimize their product distribution, improve operational workflows, patient care, reduce cost.
Banking and Financial Services. Banks can discover new insights on customer behaviour and competitor locations. It aids in reducing customer churn, helps in customer management. Financial service organizations can optimize scheduling and routes to client meetings. Companies provide the best customer experience with the newly added benefits that location insights bring to your CRM.
Logistics and Transportation. Combining customer shipment data with external geo-related data enhances transportation providers to predict potential shipping delays, address logistic issues even before they occur and therefore improve customer satisfaction.
Retail and Ecommerce: Visual mapping helps retailers break down store sales performance region by region. It compares results to competitors in the same areas. Geospatial analysis can also help track customers’ behaviour and purchasing patterns to uncover opportunities for improvement. It also enables retailers to predict the best time and location for sales and assess the potential of different locations for a new store.
Manufacturing. Supply chain companies visualize their CRM data by showing customers, suppliers, orders and deliveries on the map.
Ending Notes
Geoanalytics brings in a new perspective that is not possible to showcase with just reports and charts. Spatial data helps users unravel new sides and produce more effective outputs to showcase to customers. This helps craft marketing strategies, sales tactics, and other incentives that are more likely to resonate with consumers. It captures both the larger trends and the granular detail. Since Geoanalytics combines traditional analytics with location-based information. Thus, making the final output easily comprehendible to the end-user.
