Readers of this blog may have realized that Natural Language Processing (NLP) was missing from our ‘5 Data Analytical Trends To Watch For in 2018’ post. Our in-house team of predictive data analysts say it lost out to the other trends by a narrow margin. But that in no way takes away from the importance of NLP and its growing influence in the world of big data analytics. The loser by a whisker surely deserves an honorable mention, hence this 2-part post.
Customers leave behind an incomprehensible amount of data while they go about shopping. Making sense of that data and reacting in real time are the two things that will keep companies one-step ahead of their customers (and competition) in the present-day customer-centric world.
Data analytics need not stop at just looking in the rear-view mirror. 'What-If' analysis offers organizations a way of forecasting the future, with historical facts as the base. But your scenario modeling must be made efficient for best results.
Using Chatbots to Really Understand Your Customer: Chatbot Customer Journey Using chatbots do you really understand your customer journey? It’s now clear that chatbots are not just passing ship in the night. Over 2.5 billion people worldwide use messaging platforms like W
Here's how Machine Learning is being used to preserve data quality - A slideshow by Express Analytics explains you the same.
Cognitive computing today is like the embryonic chick beginning to peck its way out of the egg. – Hadley Reynolds, Principal Analyst, NextEra Research: May 2016. It’s been around for 50 years, going from the drawing board to the lab to field tests, but it’s only no
