How can you use geospatial data to identify areas of opportunity?

Data analytics aims to provide answers to critical questions about?who, what, when,?and?why. The power of geospatial analytics lies in answering?where?questions:?Where are our customers interacting with us? Where are our assets and staff deployed? Where do we have exposure to supply chain or regulatory risk?? Adding geographic context to your data helps answer where things should be:?Where should we build new store or office locations? Where should we direct more marketing spend? - Lowe’s optimized new store locations by identifying trade areas with a favorable demographic profile. - Sumitomo Mitsui Banking Corporation piloted a geospatial solution for finance, retail, and logistics clients to monitor risks from macro socioeconomic factors

A pergunta foi bem subjetiva, mas trazendo para um conceito bem espacial sobre "áreas de oportunidade" posso citar o geomarketing. Exemplo: 1. Problema: "qual o melhor lugar para instalar um shopping?" 2. Defini??o de dados: quais s?o os dados relevantes para responder essa pergunta? 3. Busca e gera??o de dados: buscar/criar camadas de informa??o geográfica dos dados definidos. 4. Análise e síntese: usar geoprocessamento e análise espacial para cruzamento dos dados e cria??o de produtos cartográficos ou modelos potenciais para resolu??o do problema.

Geospatial data can be used to identify opportunities by: >Identifying Spatial Patterns and Trends >Segmentation >Modeling the Real World >Predictive Analysis This data can be used across sectors like solar industry, utilities, restaurant chains, and social equity to identify areas of opportunity. In summary, geospatial data analysis involves collecting, combining, and visualizing various types of geospatial data. It is used to model and represent how people, objects, and phenomena interact within space, as well as to make predictions based on trends in the relationships between places. By doing so, it can help identify areas of opportunity across a wide range of sectors and contexts.

Geospatial data is a linchpin in identifying opportunities within the dynamic realm of Geographic Information Systems (GIS). GIS, a nexus of diverse verticals, offers rich prospects, especially in development. Through strategic development, GIS evolves beyond mapping, enabling process automation and seamless integration with platforms like web and mobile applications. The convergence of artificial intelligence (AI) with GIS amplifies capabilities, ushering in intelligent spatial analysis and predictive modeling. the fusion of geospatial data, technology, and multidisciplinary expertise positions GIS at the forefront of transformative innovation in spatial intelligence.

Geospatial data helps to locate the specific areas of concern that would otherwise be very difficult to locate and even access

Getting access to information about location is critical and can help you understand the factors around a location that can contribute to it's performance. Everything from sociodemographics, to road access, to nearby locations, transportation access, etc.

The phrase "80% of all data is geographic" aptly sums up the importance of the spatial component in the data we're handling today. Knowing how to harness location information will provide valuable insights in numerous applications and industries.

If you’re beginner my best advice is to narrow down your focus to what you want to use GIS for. By narrowing down your field it will be easier to pick a commercial or free GIS tool. I primarily work with assets and networks in the utility industry, so my tool of choice is ArcGIS by Esri. I suggest finding a project or goal you want to achieve and be specific. It is difficult to learn any new technology when you don't have a good place to start or a direction to head. I recommend picking a GIS technology that has a big community and the resources for you to learn. Getting involved in that community will be key. If you are farther in your journey my best advice is to be curious, learn everything you can, and always challenge the normal.

Quality of information generated using GIS tools requires high attention because quality result depends on the quality of input data sources we use. Otherwise wrong data use resulted in wrong information and may have a consequence of wrong decision.

While procedural steps remain consistent—Gather>Process>Analyze>Interpret>Visualize>Decision Point - tailoring the approach to a specific opportunity is crucial. If exploring opportunities in retail, begin acquiring data on population, income levels, employment, businesses, etc. Leverage ArcGIS (I admit bias) to standardize and format the data for analysis. Use techniques like clustering and identifying hot spots to recognize potential areas of opportunity, such as gaps in coverage or locations with high traffic. Present this information through a map to convey these insights to decision-makers. This visual will facilitate understanding, aiding in decision-making —whether it's a green light, or red light opportunity.

Here are common methods to visualize geospatial data: Maps: Create traditional maps using geographic coordinates to display spatial relationships. Heatmaps: Visualize concentrations of data points with varying colors or intensity, highlighting areas with higher or lower activity. 3D Maps: Represent data in a three-dimensional space, adding depth to visualizations for a more immersive experience. Time-Lapse Maps: Illustrate changes in geospatial data over time, ideal for showing trends, movements, or evolutions. Satellite Imagery: Utilize high-resolution satellite imagery to provide detailed views of landscapes or specific locations.

In my experience working with utilities most of their business is spatial. They have assets, people, work, & events somewhere spread over a geographic area. There are many opportunities for GIS to help solve problems and improve the way they do business - and many examples to back that up. So...GIS is an enabler in the utility industry. I believe the real opportunity for additional business value to utilities is using the analytical capabilities of GIS to create visual decision-making solutions. This can be done using the scientific analytical framework and combine that with the creative art of visualization applied across web and mobile applications. Bring the results to the decision makers. Focus on the opportunity and work backwards.

Understanding customer interactions, asset deployment, and exposure to supply chain or regulatory risks is critical for any business. Geospatial analytics answers these questions by pinpointing locations, offering insights into the geographical dynamics of business activities. AI plays a crucial role in automating information extraction for real-time geospatial insights. These insights are instrumental in diverse scenarios, from enhancing safety measures during rescue operations by guiding the deployment of firefighters to enabling autonomous or remote navigation for drones and vehicles. #GIS #AI #ML #DigitalTransformation #SpatialIntelligence #Spatialthinking

Learning languages such as Python and R increases your creativity to work with different tools and libraries. It extends the possibilities of applying series of analysis for a specific subject.

Geospatial data in Oil & Gas industry plays a key role, especially for Onshore operations. Every opportunity needs to start with a map made in GIS. GIS enables to integrate several data types from surface and subsurface that are all spatially referenced. The background of the map could be Satellite, Geomorphology, Geopolitical or Road map overlayed with Oil wells position, Oil facilities, Lease/concession boundaries and so-on. This delivers intuitive visual insight and gives an idea about the location type, availability of infrastructure, distance and many other spatial analysis..