In the digital era, no marketers can survive without mastering data, analytics, and automation; the reason is a massive surge in data generation. Suppose you look at the stats about data generation. In that case, it’s more than 2.5 quintillions of data generated every day, which equals 2.5, followed by stupefying 18 zeros according to social media today. “And by

A  few years ago, there was a time when technology in the cargo industry was limited to only matching shippers with drivers. It was just about a simple tool that conducts a few operations online to ease freight management.  “The logistics/trucking sector is followed by passenger ground (26%), shipping (17%), passenger air (14%), and railway (4%).”  However, the situation is

Data is being collected by the growing number of companies with the aim of using Machine Learning (ML). However, while most machine learning algorithms can only view clean datasets, real-world data is typically unorganized and complicated. “The ML pipeline fills in the gaps by using a multi-step system that continuously organizes and cleans original data, converts it into a machine-readable