Supply Chain Data

Supply chain data
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At Nomad Data we help you find the right dataset to address these types of needs and more. Sign up today and describe your business use case and you'll be connected with data vendors from our nearly 3000 partners who can address your exact need.
In today’s fast-paced and ever-changing business environment, supply chain management is perhaps one of the business arena's most complex and important technical needs. Organizations need to stay up to date on supply chain related data in order to control costs and remain competitive, while utilizing industry related data to build more advanced models and analytics. As such, datasets such as agricultural, commodities, geolocation, maritime, and transportation data can provide valuable insights into real-time supply chain activity. Utilizing these datasets, businesses can better understand the congestion levels at US ports in order to develop the most effective and efficient logistics strategies for their organization.

The agricultural dataset provides valuable insight into the availability of a variety of agricultural commodities from different countries, providing businesses with the information needed to track shipments of certain products that may be impacted by various global events. Such agricultural data can help businesses more accurately forecast supply and demand scenarios, while evaluating the impact of seasonality on product availability. This can give businesses a better understanding of the flow of commodities through the global supply chain and thus keep up with the ever-evolving landscape of supply and demand.

Geospatial data is also an invaluable tool for tracking the congestion levels at US ports. Because this data is sourced from satellite imagery, there is the added benefit of having access to the most precise, real-time location information. Utilizing this data, businesses can track the total number of vessels in transit, their routes and durations, their anchorages and berths, and any other discrepancies or issues that may be occurring at a certain spot. This insight into geospatial data can help organizations identify pain points in their supply chain processes, as well as optimize their existing practices for better efficiency.

Similarly, maritime data can also help businesses to track and analyze supply chain congestion in real-time. Maritime data sources such as cargo tracking databases, port information systems, weather databases, and AIS (Automatic Identification System) can all provide insight into a variety of maritime cargo-related activities. This data can help organizations gain insight into the available shipping routes, vessel speeds, traffic movement patterns, and other use case relevant information that can help them better understand the congestion activity at US ports.

Additionally, transportation data can also be utilized to gain a better understanding of US port congestion. Businesses having access to data on the quantity of inbound and outbound traffic, the types of transport utilized, loading and unloading times, and more can all provide valuable insight into supply chain congestion. This data can be utilized by businesses to gain a better understanding of their own warehouse and receiving operations, as well as to inform the design of the overall supply chain layout and operations.

Ultimately, leveraging a combination of agricultural, commodities, geolocation, maritime, and transportation data not only enables businesses to gain a better understanding of supply chain congestion at US ports, but also to have a comprehensive view of the entire supply chain process. This data can be utilized to optimize processes, increase efficiency, and reduce costs as businesses become increasingly equipped to make better-informed decisions. With this in mind, the value of these datasets is of immense value to organizations looking to stay competitive in their market — enabling businesses to gain real-time insights into the ever-evolving supply chain landscape.
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