ACS Solutions offers a range of IoT related services and solutions for businesses across applicable industry segments – Telecom, Manufacturing, Retail, Healthcare, Energy & Automotive. The offerings are directed to gain an enhanced customer experience & competitive edge through strategic digital transformations that may also involve leveraging IoT and 5G for innovative use cases.
Global trade is transforming radically, and Industry 4.0 revolution is upon us. No sector is immune to the disruptions that technology brings, and the Logistics industry is no different. The expectations have changed, especially regarding instant and real-time visibility of shipment information and speed of delivery. In order to stay ahead of the curve, shippers, consignees, carriers, logistics service providers have to gauge the changing trends in the industry and make proactive and informed decisions. The success in all of this boils down to one key component – Data.
Data, as rightly claimed, is the new oil. Industries today are thriving on it, and it is shaping how businesses are managed in modern times. However, distributed data sources make it cumbersome to use the information for analysis seamlessly. The presence of data in various schemas increases the time elapsed to fetch data as one needs to connect multiple data sources to get the required set of fields needed to perform further analytical tasks.
DataOps is a collaborative data management practice focused on improving the communication, integration, and automation of data flows between data managers and data consumers across an organization. It streamlines information, reduces the time spent in fetching data and what you end up with is enhanced business intelligence, suitable to make critical business decisions. Figure 1 below provides the workflow for DataOps.
Read this whitepaper to learn more about DataOps.
For a third-party logistics service provider, such data sources would be the Transportation Management System (TMS), Fleet Management Systems, Fleet Routing Systems, Order Management System, Dispatching, Routing, etc. The data from these systems are loaded into a data lake for modeling to generate business insights
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