Is location intelligence the end of GIS?

GIS was the foundation for businesses to begin collecting and visualising historical geographic information; LI encompasses new approaches to evaluating site data for optimal activity and predictions. To stay competitive, business executives need to focus on the intelligence from their location data, not just on the geographic information itself.

LI is the information and insights derived from geospatial data, visually diagramed by layering data spatially and chronologically. LI has become widely applicable across many different industries and segments to solve a variety of problems, including the public sector. GIS has been relying primarily on proprietary geographic datasets owned by the business.

Customer service-oriented companies use LI technology to see how to boost their business.  They considered that LI would become an extremely important tool for the growth of the enterprise; they are planning on investing in LI technology shortly.

Location Intelligence is the natural evolution of GIS

Reasons forcing this move from GIS technologies to LI:

New classes of managers.  LI is an easy-straightway to get for data analysts, data scientists, and developers when considering to integrate location data directly into their work movements and into central business decision making. GIS is restricted mainly to specialists with extensive training and official recognition. For example, with LI:

• Governments and data analysts can take the pulse of any city and make transit and emergency service decisions based on real-time data from calls and other sources.
• Business analysts can quickly deploy a location-based sales analytics app to make strategic decisions about their sales strategy.
• Data scientists can analyse and integrate abundant and more diverse sources of data into their workflow, quickly creating compelling visualisations to present their findings.

New data streams

Businesses can no longer depend entirely on their data. With the escalation of directly within-reach data flowing from outside resources, such as open data portals, IoT (Internet of Things) tools, and other data suppliers, enterprises can build easy-to-deploy dashboards and apps that help out to forecast and enhance business results. Examples:

• Streaming Data: Mobile device location, IoT device data, taxi pickup / drop off foot traffic, vehicle/transport, live transit, current weather conditions.
• Static Data: Topography, historic weather trends, Demographic, Financial, and much more.

New data sources. LI incorporates open data, real-time data sources and big data sets from all sorts of internet-connected systems, devices and sensors, many from sources external to the business. For example:

• Banks are employing credit cards transaction and demographic data to understand city dynamics.
• Insurers are implementing LI, weather data to make real-time decisions on how to reinforce their policy-bearers through a natural disaster.
• Real estate shareholders make use of LI and open transit data to assess new prospects for growth.

New techniques of analysis.  LI involve new approaches to examining location data for business process efficiencies and forecast, while traditional GIS analysis methods focus on reporting historical geographic information. For example:

• Spatial collecting can be depleted to build sales regions for a better appreciation for sales demands.
• Data scientists are making better routes for their services.
• Businesses can pinpoint areas of people who go further than traditional geographic borders.

CONCLUSIONS

Location Intelligence encompasses unlimited possibilities on businesses operating an extensive selection of dynamic data streams for their visualisation and analysis, rather than static information alone from a particular source. Your company needs to make a shift now!