Big data

A large volume of both structured and unstructured data that cannot be analyzed with traditional data mining techniques

Every day 2.5 quintillion bytes of data are created. Nearly every digital action — searching online, using the GPS, posting on social media, or sending an email — leaves a data trail and adds to a person’s digital footprint.

In the digital world, related data items are bundled into collections of data termed “data sets”. When these data sets get too big and complex, they can no longer be processed by traditional computer applications or database engines. Known as “big data”, they require business intelligence software to manage.

Big data analytics provides an unprecedented level of customer insight that all businesses can use to lay out their future growth strategies by predicting trends and consumption patterns.

Fast food chains are tapping on big data to customize their drive-through menus such that it promotes items that can be prepared quickly when traffic is heavy, comfort food on a cold day, or refreshing items on a sweltering hot day.

Banks are using it to tailor their customer offerings and digital banking experience on an individual level, and also to manage compliance obligations.

For the logistics industry, big data offers the opportunity to create a transparent and efficient supply chain by enabling real-time route optimization, crowd logistics and a personalized customer experience.


Download this trend report to explore the implications and use cases of Big Data Analytics in logistics.

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