Benny Ronald Emor, S.T., M.TI. was the main speaker for the Kuliah Umum with Sekolah Vokasi Universitas Gadjah Mada (UGM). Benny graduated with a Bachelor of Science in Geodesy from UGM in 2006 and has over 12 years of expertise in geographic information systems, geodatabases, spatial analytics, and system integration.
Benny worked in a variety of industries before joining Bhumi Varta Technology, including mining, palm plantations, real estate, IT consulting, and the retail sector. His experience equips him with an in-depth understanding of not just mapping and aerial photography, but also location intelligence and company growth.
This talk show mainly explained in-depth information about location intelligence especially that are available as one of the services in BVT technology. Location intelligence is the process of visualizing geographical data to discover patterns and connections that may be utilized to make decisions. Using geographic information system (GIS) technologies, location intelligence provides data-driven insights across a wide range of use cases.
When combined with other location data sources such as customer behavior and GPS systems, location intelligence enables corporate and government analysts to improve their strategic position. Spatial analytics assists the public and private sectors in detecting patterns and trends related to particular business requirements, allowing them to make more effective strategic choices. Location intelligence has integrated GIS software, big data spatial, spatial analysis, and machine learning analytics into a single platform.
Machine learning is also further explained in the talk show. Optimize the value of data by using machine learning to discover business trends, anticipate and forecast future events, and determine the optimal approach for maximizing company performance and profitability.
Location data as well mentioned in this event. Geospatial data, or location data, is a record of our actions and the locations of those actions. When we look at a map, it informs us where people and things are in respect to a certain geographic place, whether they are in the air, on the ground, at sea, or beneath our feet.
It is also known as geographic positioning. However, in order to remain competitive, company leaders understand that they must concentrate on the intelligence derived from their location data rather than simply the geographic information itself. Geographic information systems (GIS) laid the groundwork for companies to begin collecting and visualizing geographic information.
There are three primary reasons driving the transition from geographic information systems to location intelligence.
New data streams
Data from all sorts of internet-connected systems, devices and sensors, many of them from external sources, is included into location intelligence in the form of open data, real-time data streams, and large databases. The company’s geographic information system has depended mainly on private geographic datasets held by the company.
New method analysis
When it comes to business process optimization and prediction, location intelligence uses innovative ways of evaluating location data, while conventional GIS analysis methods concentrate on providing historical geographic information.
New classes of users
Developers, data analysts, and data scientists that want to integrate location data directly into their workflows and key business decision making now have instant access to location information. Geographic information systems (GIS) are primarily the purview of experts who have received significant training and certification, typically via recognized academic institutions. Their contact with key business operations is often handled through reports, which must subsequently be interpreted in order to be useful to decision makers.
Business operation analysis on the other hand creates strategic business analysis by integrating data from consumer, merchant, geographic, demographic, and other sources. This analysis functions to discover white space analysis (gaps between market penetration and availability), the relationships of customer behavior with spatial data, operations analysis (find gaps between scope and operating resources), uncover hidden potential relationships between merchants and customer behaviors, and many more.
Grid analysis is also often viewed as a marketing strategy. Using location intelligence, you may profile particular specified regions, examine a variety of defined criteria, and generate statistical and geographical analysis pertaining to those defined variables. Location intelligence may then be integrated with user data in order to identify appropriate advertising possibilities, campaigns, and merchant acquisitions depending on the information gleaned from the integration. Not only that, with the huge collection of POI (Point of Interest) data, users will be able to contribute more to society, as they will have more choices in executing the most appropriate acquisition approach.
In the view of sales support, it will help them to maximize prospective sales, create a calendar of activities for the sales team that is based on a variety of relevant factors, optimize the daily routes used by the sales team in order to maximize efficiency, monitoring of sales force everyday activities in real time for the purpose of subsequent analysis, optimization, and coaching is also provided, and regular reporting that focuses on the statistical performance of the whole sales team or of individual sales representatives.