How to Use Transportation Analytics and its benefits
Wednesday, September 8, 2021
Through data analytics it's possible to improve vehicle performance, reduce costs, improve processes, establish strategies, optimize routes and times, and foresee and identify problems, among others.
Transportation analytics takes a variety of data ecosystems, helping industry leaders to use advanced analytical techniques such as machine learning
, Big Data
data to optimize business strategies in the sector.
Predictive analytics in enterprises can answer questions such as "What is the best possible outcome?" or "What is the most efficient route to effective distribution?" Foreseeing from events that may affect transportation
such as weather, road closures, strikes, maintenance, traffic, risk zones and estimate the impact of development projects to help identify an alternative project without obstructing mobility.
"Image representing a visualization of Foot Traffic
for a specific location in U.S. California."
With the growth of multimodal transportation, the need for different transportation routes analysis are essential.Highways
Geospatial data and machine learning can be used to analyze where, why and when accidents occur, determine future road projects, keep track and identify pedestrian and vehicles movement patterns behaviors, etc.
analysis applied to the railway sector can improve safety, scheduling, automatic planning, network and ticket management, among many others.
Strategies can be implemented to improve employee performance, identify peak and off-peak periods, optimize routes
, costs and maintenance liabilities, design an efficient infrastructure model, or even classify travelers to better maximize sales.Port
With Big Data
and machine learning, you can improve vessel monitoring for more effective voyage planning and execution, forecast weather stations, optimize fuel costs, establish maritime routes that reduce costs and times, etc.
There are many challenges facing the transportation sector today that can be solved with business intelligence
analysis focused on transportation.
Data Driven we integrate data analysis from multiple sources, minimizing logistical
problems and automating a predictive model to project future trends, identify business needs and build long-term strategies to maximize revenue.
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Location analytics to Optimize Distribution Routes
Location intelligence through techniques based on Big Data collects spatial data in order to improve the decisions made in logistics centers, allowing the use of location and its related data points, creating solutions and optimizing distribution routes.
This new technological tool finds its immediate application in space-dependent businesses, such as
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supply chain crisis
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Problems with Last Mile-Delivery Processes?
Several companies, especially in the retail sector, have realized that they need to challenge traditional last-mile delivery solutions in light of recent advances in technology tools.
With the help of
that gives access to aerial,
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planning delivery routes
more efficiently based on fuel costs, travel time, road tolls, etc.
POI Analysis in the Retail Sector
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